International audience

An analysis of the potential and limitations of interferometry using near-specular signals of opportunity (SoOp) remote sensing systems for surface height measurement is presented. Results from an attempt at “repeat pass” interferometry with NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission conducted on September 30, 2019, are reviewed, along with models for the sensitivity of the interferometric phase to surface height in “single-pass” multiple-antenna observations. An analysis of 58 CYGNSS “raw I/F” tracks is reported for which single-pass interferometry is feasible given a specular point’s location in the overlap region of CYGNSS’s two receive antennas on a selected satellite. The observations and models developed highlight the impact of parameters such as the baseline distance separating the two antennas, the size of the scattering footprint, the incidence angle, the measurement bandwidth, and the measurement SNR. The results describe the potential of near-specular SoOp interferometry but also demonstrate factors that can limit the sensitivity achievable to a fraction of that obtained by interferometric synthetic aperture radars (SARs).

A method for detecting and geolocating terrestrial GPS L1 band interference sources using Cyclone Global Navigation Satellite System (CYGNSS) mission Level-1 noise floor estimates is described. Evidence of interference sources and their signal properties is first presented using CYGNSS’s special raw I/F acquisition mode. The associated Level-1 data is shown to require additional processing steps to provide information on the RFI contained. A “EIRP correlation” approach combined with a spatial anomaly clustering method is developed and applied to CYGNSS Level-1 noise floor data extending from August 1st, 2019 to April 1st, 2025 to produce a daily radio frequency interference (RFI) product on a ≈10 km grid and to geolocate the sources contained. The results reveal more than 25 unique GPS L1-band interferers over the analysis period, with the majority located within the MENA (Middle East and North Africa) region as well as Myanmar. Use of the method for detecting and geolocating interference sources beyond CYGNSS’s nominal northernmost 38°N latitude coverage is also demonstrated. The results highlight how GNSS-R observations can be instrumental in monitoring and understanding the GNSS RFI environment.

We report a study of radio frequency interference (RFI) in the GPS L1 band (1575.42 ± 2 MHz) using spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) data. An examination of the “noise” levels reported by both Spire, Inc. and CYGNSS (Cyclone Global Navigation Satellite System) standard Level 1 products is first presented that shows clear evidence of RFI contributions. Data from 498 acquisitions in CYGNSS’s special raw I/F (Intermediate Frequency) mode is then used to examine RFI source properties in greater detail. Both kurtosis and cross-frequency algorithms are applied with the raw I/F data to detect the presence of RFI. The results suggest that up to 25% of the acquisitions considered contain RFI, with both “narrow” and “wideband” sources of varying amplitudes observed. The results provide insights into RFI source properties in the GPS L1 band as well as methods by which the RFI can be detected.

Data from the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission have shown promise for the retrieval of soil moisture, and many soil moisture products using CYGNSS data have been developed. In this work, we present a merged product that combines several CYGNSS soil moisture products using a minimum variance estimator (MVE). The MVE identifies an optimal weighted averaging scheme based on the error covariance characteristics of the CYGNSS soil moisture products. The error covariance matrix is computed using two reference datasets: soil moisture data from the Soil Moisture Active Passive (SMAP) radiometer and in situ soil moisture data. The results from each of these provide insights into both the performance of the merged product and the individual input CYGNSS products. Overall, the merged product offers better performance than any individual CYGNSS product while also offering better temporal resolution than SMAP. The results of this work also demonstrate that the use of the MVE is a compelling technique for soil moisture applications.

Doppler scattering simulations from sea-like surfaces are sensitive to non-linear hydrodynamic effects in wave propagation. Two commonly considered approaches to introduce such non-linearities – the Creamer transform and the Choppy wave model – are examined in this paper. It has been observed that the two models yield simulated Doppler spectra with conspicuously different centroids. Based on the modulation transfer function theory for the Doppler moments of sea backscatter, it seems plausible that such a behavior could result from model differences in the hydrodynamic modulation of smaller, scatter-producing ripples by larger waves. We perform numerical experiments to measure the corresponding hydrodynamic modulation transfer functions (HMTF). An established approach uses a single-harmonic large-scale surface. A correlation-based technique is also proposed that allows HMTFs to be estimated in Monte Carlo simulations of full-spectrum ocean-like surface profiles. Both methodologies show the Creamer HMTF values to be significantly larger than their Choppy-wave counterparts. Estimates made with ocean-like surfaces are also found higher than those based on the solitary-wave approach, particularly for the Creamer model. Application of the first-order Romeiser-Thompson theory with the estimated HMTF values produces Doppler shifts that are in general agreement with those observed in exact scattering simulations using either surface representation. The results of the study reveal considerable differences between the hydrodynamic modulation effects of the two surface models and demonstrate that those disparities are important contributors to the observed deviations in Doppler centroids. More work is required to conclusively determine a preference of one model over the other.

Methods for promoting flexible use of the radio frequency spectrum in microwave radiometry are examined in order to assess the potential for future spectrum sharing paradigms. Results are shown that suggest that geophysical product retrieval performance can be maintained under a variety of channel frequencies and bandwidths.

The development of soil moisture retrieval algorithms for the upcoming NASA/ISRO SAR mission motivates investigations into soil surface scattering effects and their influence on soil moisture retrievals. To better understand the conditions that impact retrieval performance, an investigation is performed into the second-order solution small slope approximation (SSA2) for rough surface backscattering. Scattering amplitudes are calculated for varying soil moisture and surface roughness conditions and compared to the first-order solution. The results show the ability of the second-order solution to model cross-pol scattering and help pinpoint physical conditions that may influence soil moisture retrievals. Overall, the results suggest that the first-order SSA solution should be applicable under the physical conditions where NISAR soil moisture retrievals are expected to be performed.

Doppler spectra obtained from simulations of ocean-like surface bistatic scattering are shown under the first order small slope approximation of rough surface scattering. Spectral properties are examined as a function of wind speed, polarization, and observing geometry in order to assess the potential for the bistatic remote sensing of various sea surface properties.

Recent updates in the use of 0.5-2 GHz microwave radiometry for remotely sensing Earth’s cryosphere are reported. These updates concern measurements and modeling of the spectral properties of brightness temperatures for geophysical regions such as ice sheets, sea ice, ice shelves, and others. The results are intended to support the continued development of 0.5-2 GHz passive microwave mission concepts for future deployment in space.

The spectral description of the wind-roughened ocean surface usually involves an omnidirectional spectral model and an azimuthal spreading function that describes the fraction of the waves of a certain length propagating at a given angle with respect to the wind direction. A number of such functions have been introduced and refined over the years. We use the 2nd-order Small Slope Approximation (SSA2) to calculate and compare the backscattered normalized radar cross sections resulting from several of them. In the process, the same Hwang omnidirectional spectrum is used. The SSA2 allows evaluating both co-polarized and cross-polarized backscattering cross sections. This study focuses on L and Ku radar bands and wind speeds between 5 and 9 m/s and covers a wide range of incidence angles. The results are compared with geophysical model functions where available.

Space-Air-Ground Integrated Networks will facilitate seamless user experiences across a variety of 6G applications. The deployment of these networks will necessitate new approaches to spectrum allocation. Spectrum access by passive microwave sensors for earth-based and space-based scientific applications represents a spectrum use application having unique attributes that motivate consideration of spectrum sharing between these “incumbents” and commercial users to ensure the most efficient utilization of available frequencies across applications. Toward this end, we propose an economic framework where incumbents have priority use, with a primary and secondary commercial tier underneath. For commercial users, the option to join the primary tier is based on a model of short term post-paid leases of spectrum, while the secondary tier is available to join at no cost. Using a joint game-theoretic and queuing-theoretic model, we find that for practical parameters the revenue maximizing equilibrium is: 1) stable in the Evolutionary Stable Strategy sense; 2) associated with the maximum priority upgrade fee customers are willing to pay; 3) associated with an equilibrium where all customers wish to join the priority class; and 4) socially optimal. We validate our findings leveraging trace data from satellite radiometers operating in the vicinity of Boston, Massachusetts.

Ice shelves are important parts of the cryosphere that influence ice sheet dynamics and mass loss. The internal temperatures of ice shelves are currently known only from a few borehole sites or from glaciological models. Microwave radiometry in the 0.4–2.5 GHz range is capable of receiving thermal emissions from deep within an ice shelf and thereby providing information on internal temperatures. This letter reports modeling studies of the brightness temperature of the Ross Ice Shelf (RIS) from 0.4 to 2.5 GHz that provide insight into the potential of microwave radiometers for measuring ice shelf internal properties.

The use of a “time-series ratio” soil moisture retrieval approach is under consideration for the upcoming NISAR mission’s soil moisture product. As such, it is of interest to characterize the algorithm’s anticipated error budget as part of pre-launch activities. This paper develops an error model to estimate retrieval errors for the proposed algorithm. The model accounts for error contributions from speckle and thermal noise as well as uncertainties that arise as part of the retrieval process. Spatial and temporal behaviors of the retrieval errors are determined using a SMAP-based soil moisture climatology. The results show that soil moisture retrieval errors from the time-series ratio method meet the 0.06 m3/m3unbiased root mean square error (URMSE) performance metric established for the NISAR soil moisture product.

Applications involving the measurement of specular reflections from the Earth’s surface have recently renewed interest in the coherent reflection coefficient of a rough surface, particularly in the limit where the reflection coefficient becomes small. In this letter, a statistical model is first presented that characterizes the number of surface realizations required to obtain a specified precision in estimating the coherent reflection coefficient; the model shows that the number of realizations increases significantly as the coherence of the reflected signal decreases. A study of rough surface reflection coefficient amplitudes is also reported. The Kirchhoff Approximation (KA) is frequently used to describe the coherent reflection coefficient amplitude as a function of the angle of incidence and the surface root-mean-square (rms) height relative to the electromagnetic wavelength. KA predicted horizontally polarized reflection coefficients are compared with those obtained from Monte Carlo method of moments (MOM) simulations using 1-D perfectly conducting surfaces described as stationary Gaussian random processes with a Gaussian correlation function. The comparisons show reasonable agreement between the KA and MOM results for a variety of observing scenarios and reflection coefficient amplitudes, and an improved level of agreement if a correction to the KA prediction derived from the small slope approximation (SSA) theory of surface scattering is included.

Full-wave simulations of the effective permittivity of firn aquifer and wet snow at L-band are reported. The Monte Carlo simulations are carried out for bicontinuous media embedded in a sphere, and the scattering cross section and absorption cross section are calculated. By averaging over realizations, the effective permittivity is extracted by comparing it with Mie solutions. The simulations are validated by using three numerical methods of 3-D solutions of Maxwell equations: finite difference frequency domain (FDFD), finite element method (FEM), and the discrete dipole approximation (DDA). Full-wave simulation results are compared with those from the classical Maxwell–Garnett and Polder–van Santen mixing formulas. The results show large differences from mixing formulas when there are large permittivity contrasts between the background medium and the scatterers, which are scenarios in aquifer and wet snow. The significance of these results is examined for the L-band microwave remote sensing of terrestrial wet snow and aquifer in polar regions.

Airborne 0.5–2 GHz brightness temperatures were collected along a transect of the Priestley Glacier, Northern Victoria Land, Antarctica that coincides with previously acquired 189–199 MHz depth sounding radar data from NASA’s Operation IceBridge (OIB). The measured brightness temperature spectra evolve from negative spectral gradients (brightness temperature decreases with frequency) over the inland ice sheet and upper reach of the outlet glacier toward positive spectral gradients in the central region of the glacier. The spectra then increase almost linearly with frequency over the floating portion of the glacier terminus. The positive spectral gradients are more similar to sea ice on the ocean as compared to the grounded interior ice sheet. Comparison with modeling studies at Ross Ice Shelf sites where physical temperature has been measured in boreholes shows that positive gradients are to be expected where glacier ice overlies a water base. Calculations of radar reflectivity support the assumption of patchy regions of basal water and help to resolve ambiguities associated with processes such as interface roughness and near-surface firn layering.

Here we show the initial design and results from MAPPERR: The Multi-frequency Active Passive Polar Exploration Radar-Radiometer. MAPPERR addresses fundamental limitations in traditional ice-penetrating radar sounders and microwave radiometers stemming from non-unique contributions of different glaciological conditions. By utilizing active radar channels at 2, 22, 330, and 1000 MHz MAPPERR is designed to disentangle basal roughness and basal material conditions, while also providing important constraints on englacial temperature via measurements of attenuation. Passive radiometer channels at 330 and 1000 MHz provide additional constraints on englacial temperature via measurements of thermal emission and attenuation. Here, the system design is described and initial field results from campaigns in Svalbard, Iceland, and Antarctica are presented.

Ice sheets are fundamental components of the Earth’s system that impact the climate through their contribution to global sea level. Knowledge of an ice sheet’s internal temperature is essential to improve understanding of its dynamics and hence its mass balance. We present an over-complete set – termed a dictionary of functions– for approximating the ISSM-simulated vertical temperature profiles obtained over the Greenland continent. Next, we present an algorithm to retrieve the internal ice-sheet temperature from brightness temperature measurements obtained. Finally, we compare the root mean square error (RMSE) between the recovered temperature profile using the Robin model, extended Robin model and Dictionary based method and the true temperature profile by varying the radiometric noise in the brightness temperature. We quantitatively establish that the proposed dictionary based method outperforms the Robin model in recovering the ice-sheet temperature profile from radiometic measurements.

This work reports a case study of the use of synthetic cyclone models for the development, assessment and validation of global navigation satellite system reflectometry (GNSS-R) wind speed remote sensing algorithms using a cyclone global navigation satellite system (CYGNSS) data record extending from 1 August 2018 to 31 December 2022. Synthetic cyclone models are shown to be useful in assessing the high wind speed sensitivity of CYGNSS’s v1.0, v2.1, v3.0, v3.1, and future v3.2 normalized bistatic radar cross Section (NBRCS) products due to the extended matchup dataset of high wind speed information that is obtained. The models are also shown useful in investigating the impacts of specific error corrections terms and in the development of level-2 geophysical model functions (GMFs) for the retrieval of ocean surface winds.

Measurement of ice-sheet thermal state via microwave remote sensing techniques has the potential to provide critically needed observations on englacial temperature at the local and continental scale. Better constraints of the vertical englacial temperature structure are needed to improve understanding of thermomechanical processes, ice rheology, and basal sliding, and to reduce uncertainty in interpretations of basal conditions such as material, roughness, and thermal state. We investigate the potential to combine active and passive microwave remote sensing techniques, namely ice-penetrating radar sounding and microwave radiometry, to enable more precise, accurate, and robust measurement of ice-sheet thermal state across widely varying thermal regimes. We simulate the effects of englacial temperature profiles on the attenuation and brightness temperature and explore the performance tradeoffs for joint radar-radiometer system architectures. Our analysis shows that active and passive microwave measurements have complementary sensitivities to englacial temperature as a function of depth, and that a ground-based joint radar-radiometer system can reduce the requirements and complexity demanded of each single instrument.

Lidar elevation maps are utilized in a bistatic electromagnetic scattering model of the Cyclone Global Navigation Satellite System over San Luis Valley in Colorado, USA. The results are compared with results generated using the Shuttle Radar Topography Mission (SRTM) 1 arcsecond global digital elevation model (DEM). The high resolution lidar maps are also used to generate maps of surface roughness at length scales finer than the horizontal resolution of SRTM. Model results using these maps illustrate the importance of the spatial variation of surface roughness on reflectometry signals. Results also highlight the shortcomings of using SRTM in scattering models and show improvements when a lidar DEM is used.

A recent ship-based field campaign demonstrated the use of a maritime multi-channel reflectometer using Sirius-XM broadcast radio downlinks as Signals-of-Opportunity. This campaign involved the collection of a large data set of bistatic ocean surface scattering measurements, which coincided with ground truth data detailing local oceanographic parameters. The experiment was unique in that most of its measurements were taken well outside the plane of incidence, with illumination from an oblique angle. This study offers a novel opportunity to explore the fidelity of electromagnetic models (coupled with oceanographic models) to predict radar scattering in these unique geometries. Match-ups are shown between measured and modeled bistatic normalized radar cross sections and range profiles, with the intention of both 1) supporting shore- and pier-based reflectometry through bistatic surface scattering model validation and 2) demonstrating the utility of using reflectometry for oceanic remote sensing from a sea-faring vessel.

In literature, a variety of models, representations and formalisms exist that describe electromagnetic waves and their interaction with media. The choice of model often depends on the required properties of the electromagnetic wave, e.g. the degree of polarization or whether the modeled electromagnetic wave is described coherently (amplitude and phase) or incoherently (only amplitude). In this study, we propose a more unified theoretical framework that can represent all cases of coherent, non-coherent, fully polarized, partially polarized, and non-polarized electromagnetic waves. The novel framework also represents them in such a way that the principles of energy conservation and conservation of polarization states are already manifested in the equations.

The Soil Moisture Active/Passive Mission was launched in 2015 to provide estimates of global surface soil moisture from its L-Band radiometer measurements. The digital backend included in SMAP's radiometer enables radio frequency interference (RFI) to be detected and filtered in real time. The six-year record of SMAP's RFI data available now allows global monitoring of the RFI environment and its changes over time. An automatic tool has been developed for this purpose that generates a table listing the most persistent and strongest sources. This paper provides an analysis of these tables to examine the evolution of the RFI environment over time. The use of the tables generated for reporting RFI sources to national authorities is also discussed.

The National Aeronautics and Space Administration (NASA) - Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) mission plan to launch a SAR operating at L- and S-band with a 12-day repeat frequency. A global soil moisture product at 200 m spatial resolution derived from 200 m NISAR radar measurements is currently under development. Although several retrieval algorithms are being investigated, this paper focuses on a “time series ratio” retrieval approach. In order to understand and assess the performance of this algorithm, an error model has been developed and is reported in this paper. The model is applied to examine errors as a function of the instrument characteristics and for a given location. Initial progress in including vegetation effects and in predicting errors as a function of spatial location is also described.

Analyses of GNSS-Reflectometry data sets have demonstrated that coherent signals can be observed over land areas. To fully interpret those measurements, forward modeling of the scattering of the GPS signal over land can be performed. Scattering theories rely on several parameters, but the surface roughness is one of the main unknowns that is usually derived from Digital Elevation Models (DEM). However, standard DEMs are too coarse to provide information on the finest scales of surface roughness. Airborne lidar measurements can provide DEMs at higher spatial resolution and better vertical accuracy than those available from standard DEMs. This paper presents two airborne lidar campaigns that were conducted to support CYGNSS land cal/val activities in the San Luis Valley, CO (where mostly incoherent returns are observed) and near White Sands, NM (where mostly coherent returns are observed). An initial comparison of surface statistics at the two locations is also provided so that insight can be obtained into the surface characteristics necessary to generate either coherent or incoherent scattering for GPS signals reflected from land surfaces.

Accurately measuring the vertical temperature profiles of ice sheets and glaciers is important for providing observational constraints on how temperature impacts ice rheology and flow. Directly measuring englacial temperature is challenging, often involving resource-intensive boreholes. Ice-penetrating radars and radiometers have been utilized independently to probe englacial temperatures, highlighting the potential of remote sensing to collect glacier- and catchment-scale temperature data. Here, we investigate the sensitivity to temperature at depth of active and passive microwave systems and highlight the benefits of combining their measurements to constrain and improve top-to-bottom temperature retrievals. These simulations allow us to understand how each instrument performs when applied to the unique electromagnetic and geophysical properties found on an ice sheet, enabling us to tailor our system design and implementation in a target-informed acquisition and analysis approach.

For understanding englacial hydrology and its impact on ice sheet mass balance, observations of the liquid water content (LWC) within the ice sheets are needed. Earlier studies have shown the complementary nature of multi-frequency microwave radiometer measurements to detect subsurface LWC distribution in addition to surface LWC, which is critical for understanding the seasonal melt dynamics of ice sheets. In this study, we used 1.4 GHz brightness temperature (TB) measurements from the NASA Soil Moisture Active Passive (SMAP) satellite, and 6.9, 10.7, 18.9, and 36.5 GHz TB measurements from the JAXA Global Change Observation Mission-Water Shizuku (GCOM-W) satellite to investigate the multi-frequency response at pan-Greenland scale. The melt indications derived at different frequencies show trends consistent with persistent seasonal subsurface melt water and delayed subsurface refreezing of the seasonal melt water. The result suggests that the seasonal subsurface persistent melt water occurrences that are not captured by the high-frequency retrievals are both temporally and spatially very significant.

This paper presents a novel probabilistic method that is used to identify low-SNR measurements in a cloud profiling radar application and terminate them before completion to save resources. The method uses a statistical model to predict the final SNR level of a measurement in progress and terminate it if it falls below a specified threshold at a specified level of confidence. The method is applied in a simulation study in which radar backscattered power profiles are obtained from CloudSat radar data, and is shown to achieve favorable performance.

L- and S-band observations from NASA's Passive/Active L/S band (PALS) sensor from the SMEX02 campaign were used to estimate soil moisture. The retrieval process is based on the “alpha approximation” method. This method utilizes a time-series of normalized radar backscatter measurements as well as ancillary information to estimate soil moisture over the Walnut Creek watershed. The resulting retrieved soil moistures are compared to in-situ soil moisture measurements at multiple test sites within the watershed. The calculations show reasonable results for both L- and S-band and provide further insight into the use of L- and S-bands for the upcoming NASA/ISRO mission.

A method for determining the cutoff wavenumber used in the geometrical optics theory of scattering from a random rough surface is presented. The method is based on the “alpha stable distribution” approach described in previous studies, and yields a cutoff wavenumber that depends on the spectrum model applied, the angle of incidence, and the frequency of interest. Use of the cutoff wavenumber so determined is found to improve agreement between predictions of the geometrical optics and physical optics theories of near specular scattering from the sea surface in some situations.

In this paper, we investigate the use of parametric wind fields derived from two versions of Level-2 (L2) wind data obtained from the Cyclone Global Navigation Satellite System (CYGNSS) mission on storm surge modeling. Specifically, storm surge simulations are performed for Hurricane Michael (2018) with the ADCIRC+SWAN model using wind data derived from the two aforementioned L2 CYGNSS data sets and from the National Hurricane Center's Best-Track (BT) data. Results obtained from the three wind fields are compared with a set of high-water marks provided by the US Geological Survery (USGS), where it is shown that the more recent (pre-release version 3.1) L2 CYGNSS product offers comparable accuracy to that of BT-based wind fields and provides significant improvement over the earlier (pre-release version 3.0) L2 CYGNSS product in terms of computed storm surge levels.

The NASA ISRO Synthetic Aperture Radar (NISAR) mission is currently under development and will provide global L-band radar observations that will be helpful for various soil moisture applications. The final NISAR soil moisture product will have 200m spatial resolution with 12-day exact revisit time. A time-series ratio algorithm was implemented using NISAR simulated UAVSAR data collected during the SMAPVEX12 field experiment. In this paper, the performance of the time series ratio algorithm was assessed using in situ observations. Performance of the soil moisture retrieval algorithm was also assessed for dual polarization and quad-polarization observations modes.

Wideband microwave radiometry holds promise for new in-sights for passive remote sensing of snow packs. We report on a plot-scale, season-long field experiment using two wide-band microwave radiometers operating with about 1 GHz of bandwidth at L-band frequencies. Despite considerable ra-dio frequency interference (RFI), there remains many 100's of MHz of usable bandwdith for measurement. We report on the wideband signatures of a snowpack that varies in depth from no snow to more than 57 cm deep.

The physical process of GPS signal reflection from Earth's land surface is of interest in order to support the development of land applications using GNSS-Reflectometry (GNSS-R) data. A key question is understanding when GNSS-R land returns should be examined in terms of their reflectivity or normalized radar cross section (NRCS). An airborne lidar DEM obtained near White Sands, NM is used to compute surface roughness properties. The roughness map is then correlated with the recurrence of coherency derived from three years of CYGNSS observations. The results show that “medium scale” rms heights within the first Fresnel zone of less than < ~ 10 cm are associated with coherent reflections. Initial analysis of a raw IF data track further demonstrates the decrease of coherence with increased surface roughness.

The density profile of a polar ice sheet is an important parameter for the estimation of ice mass balance. Wave reflections caused by density variations are also a key uncertainty in the retrieval of ice sheet temperature profiles in Ultra-Wide band radiometry. In this paper, we examine different firn density profile models and analyze the subsurface reflections they cause using an analytical partially coherent approach. We also examine firn density profiles obtained from borehole measurements, from past UWBRAD modeling studies, from a community firn model, and from snow radar echo measurements. In previous studies, the ice sheet has been model as a 1D random medium with density variations in depth. However, horizontal density variations also exist, so that the ice sheet is a 3D random medium. Analyses using the partially coherent model show that in the presence of horizontal fluctuations, contributions from short scale variations vanish as the horizontal correlation length decreases due to the diffraction of waves.

In this paper, an Analytical Kirchhoff Solution (AKS) and Numerical Kirchhoff approach (NKA) are used to study coherent and incoherent land surface near specular scattering at L and P bands. The AKS model includes both coherent and incoherent waves, and includes the effects of topographic slopes and elevations. The land profile is modelled as a summation of three scales of surface roughness corresponding to “microwave”, “fine topography”, and “coarse topography”, where the microwave roughness and fine topography are treated as random processes while the coarse topography is deterministic. An airborne lidar survey performed over the San Luis Valley, CO is used to obtain surface roughness information for the simulation results of$\mathrm{P}$and L-band scattering. Results using the lidar surface data show that coherent reflection can dominate returns from a 5 km by 5 km area at P band, while incoherent scattering dominates L band returns in the same scenario.

This paper is a preliminary study of estimation of Antarctica Dome-C ice sheet properties using 0.5-2 GHz Ultra Wide Band Software Defined Radiometer (UWBRAD). The estimated ice sheet parameters include the vertical temperature profile and stochastic parameters that describe the density fluctuations within the ice column. The borehole measured temperature profile is used as a prior. The inversion uses regularization to incorporate both the prior borehole measurement and the UWBRAD data in the cost function. A hybrid model that use both cloud and partially-coherent models is chosen for this study as the forward model [1]. Since the partially-coherent model has a long computation time, a neural network is trained to replace the hybrid forward model and this neural network is used in the inversion. A genetic algorithm inversion scheme is used.

A previously reported time-series ratio method for retrieving soil moisture information from Cyclone Global Navigation Satellite System (CYGNSS) measurements is updated to improve the algorithm used for excluding CYGNSS measurements from the time series, thereby improving the algorithm’s computational efficiency while eliminating the requirement for contemporary soil moisture information from Soil Moisture Active Passive (SMAP). Daily CYGNSS soil moisture estimates are retrieved and presented on a 36-km grid over the 27-month period January 2018–May 2020 and show an overall root mean square error$\approx 4.46$%, an overall correlation for all attempted retrievals of$\approx 80.53$%, and an average correlation for individual pixels of 48.61% relative to SMAP using the updated time-series algorithm. An analysis of the errors of the updated algorithm is also provided as a function of surface properties.

Measurements of the 500–2000-MHz brightness temperature spectra of Antarctica acquired under the Ice Sheet and Sea Ice Ultrawideband Microwave Airborne eXperiment (ISSIUMAX) are reported. These data sets support the remote sensing of ice sheet properties, in particular information on the temperature profile within the ice sheet. The Ultrawideband Software-Defined Microwave Radiometer (UWBRAD) was installed on a Twin Otter aircraft, and measurements were collected on coastal areas and the interior of East Antarctica in November and December 2018. UWBRAD 500–2000-MHz brightness temperature measurements along a 1000-km path over the ice sheet are compared in this letter to forward model simulations for these locations and confirm the expected sensitivities to ice sheet parameters.

Simulation results are used to assist algorithm development for extracting the ocean surface significant wave height (SWH) from microwave scattering of satellite broadcast signals from the ocean surface. The analysis shows that the Doppler frequency spectrum width is a reliable parameter for extracting the SWH. The numerical experiments include both deep and shallow water conditions. The correlation between Doppler frequency spectrum width and SWH is robust and applicable to all wind speeds, inverse wave ages, and water depths tested in this study (5–21 m/s, 0.8–2.0, and 3 m–$\infty $, respectively).

Radar images of a 1-D perfectly conducting rough surface are compared for monostatic and for the equivalent bistatic imaging configurations. The results show that, while first-order “single” scattering images are largely similar; higher-order scattering effects can show differing signatures for these two imaging modalities.

Ocean wind speed and/or wind vector measurements from the cyclone global navigation satellite system (CYGNSS), advanced scatterometer (ASCAT), and WindSat satellites are used to investigate diurnal wind variations over the tropical ocean using a method previously reported for diurnal amplitude estimation. The resulting diurnal variability in wind speed is examined in terms of its spatial and temporal properties. The results also show that the remotely sensed diurnal amplitudes obtained are largely consistent with those predicted by the existing reanalysis products such as the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5.

Backscattering from rough soil surface has important applications to the remote sensing of soil moisture and snow water equivalent (SWE), To extend simulations to Ku-band, we have performed full wave simulations up tokh=15. Results are simulated for various profiles and show that the scattering at C-, X-, and Ku-bands is influenced by both scales of centimeters roughness and millimeter roughness. Comparisons are made between constant ratios rough surface and constant correlation length rough surfaces. The results are illustrated for both VV and HH polarizations. Simulation results are in good agreement with X band measurement data as a function of incidence angle. An illustration is used to show how the results can be used for theoretical models of rough surface scattering in remote sensing of snow water equivalent.

Airborne 500–2000-MHz radiometric measurements recorded in high-latitude regions (portions of Greenland, Antarctica, and Northern Canada) are used to provide insight into the radio frequency interference (RFI) environment that can be expected for future radiometer missions operating in this frequency range. Statistics of the RFI environment are reported in terms of the likelihood of a specified bandwidth measurement containing RFI corruption. The results indicate that wideband radiometry from 500 to 2000 MHz is viable for science applications in the majority of the regions surveyed.

A comparison of three different electromagnetic scattering models for land surface delay-Doppler maps (DDMs) obtained from global navigation satellite system reflectometry (GNSS-R) along a Cyclone Global Navigation Satellite System (CYGNSS) track in the San Luis Valley, Colorado, USA, is presented. The three models are the analytical Kirchhoff solutions (AKS), the Soil And VEgetation Reflection Simulator (SAVERS), and the improved geometrical optics with topography (IGOT). Common inputs to the three models were defined by using field samples of soil moisture and texture, soil surface roughness measurements, and a digital elevation model (DEM). The resulting peak reflectivity profiles of the models and the CYGNSS data all had a range of 10 dB along the selected track, mainly due to the influence of topography. The reflectivities obtained from all three models agreed with one another to within 2.4 dB along the full length of the track. The models also showed general agreement with the corresponding CYGNSS data, although the modeled profiles were higher than CYGNSS Science Data Record Version 3.1 by an average of 5 dB and also smoother. Additional characterization of fine-scale surface roughness is identified as an area for future work to improve model fidelity. An intercomparison of DDM structure for three selected acquisitions is also provided.

A ground-based ultra-wideband radiometer operating at 540, 900, 1380, and 1740 MHz was used to measure microwave thermal emissions from an Arctic sea ice floe as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Expedition. The instrument was deployed on a drifting ice floe near 86°N, 120°E in leg 1 of the expedition (December 2019) and observed second-year ice (potentially with refrozen melt ponds) that experienced new ice growth at its base over a ten-day period. Measured circularly polarized brightness temperatures were compared with the predictions of a radiative transfer (RT) model for a layered medium consisting of ocean, growing new ice, desalinated remnant second-year ice/refrozen melt pond, and snow layers. Characteristics of the sea ice composition used in the model were determined fromin-situmeasurements. Comparisons of the measured and modeled wideband brightness temperatures showed good agreement consistently over the observation period and for various off-nadir observation angles. The results demonstrate the capabilities of 0.5–2 GHz microwave radiometry for observing sea ice properties and also show the impact of a saline ice layer at the ice bottom on the measured brightness temperature.

Arctic sea-ice thickness and salinity retrievals are simulated to explore the performance of nadir-observing microwave radiometry operating with up to 16 frequency channels in the 0.5–2-GHz frequency range. A radiative transfer model is used to create lookup tables of the circularly polarized thermal emissions of first-year (FY) and multiyear (MY) sea ice, and the performance of two distinct retrieval methods is examined. The first method retrieves only sea-ice thicknesses, while the second retrieves both ice thickness and ice salinity. Retrieval errors are simulated for both FY and MY sea ice as a function of ice thickness, salinity, and temperature to investigate the impact of radiometric uncertainty, the frequency channels used, and any errors in ancillary information. To gain further insight into Arctic scale retrieval performance, a simulated brightness temperature dataset is produced for Arctic sea ice for the period October 2020–March 2021 using sea-ice thicknesses from the SMOS-CryoSat-2 algorithm. Compared to existing sea-ice thickness retrievals obtained from 1.4-GHz microwave radiometers, the results demonstrate that 0.5–2-GHz radiometry can achieve higher sensitivity to a sea-ice thickness within the range 0.5–1.5 m for FY sea ice and enable the retrieval of multiple sea-ice parameters (thickness and salinity) simultaneously.

Although ice sheet internal temperature is a first-order control on glacier dynamics, relatively few in situ borehole temperature profiles exist. The ultra-wideband software-defined microwave radiometer (UWBRAD) was designed to estimate internal ice sheet temperature (Ti) by measuring microwave brightness temperatures (Tb) from 0.5 GHz to 2 GHz. The retrieval ofTifromTbis not straightforward, however, due in part to the complicating effects of ice density fluctuations onTb. In this paper, we report a simulation study to assess the feasibility of realizing three science goals: the retrieval of a)Tiat 10 m depth to within 1 K; b) vertically-averagedTito within 1 K; and c) the verticalTiprofile to within 1 K RMSE. Two analyses along the Greenland ice divide are presented. First, we assess the ideal UWBRADTiretrieval precision via the Cramér-Rao Lower Bound (CRLB). Second, we perform a “Virtual Experiment” (VE) using synthetic UWBRAD observations. Both the CRLB and VE analyses indicate that the science goals are achievable with the caveats that ice thickness and UWBRADTbprecision impact performance. Assuming a UWBRADTbprecision of 0.5 K, and for places where ice sheet thickness is less than 3 km, all science goals can be achieved. The results of the study provide a strong indication of the potential of UWBRAD to provide valuable Greenland ice temperature profile information to the scientific community.

Numerical experiments are carried out to explore the retrieval of ocean surface significant wave height (SWH) with the Doppler spectrum width (DSW) of microwave bistatic scattering from the ocean surface. Variations of DSW with incidence and scattering angles, wave height, wind speed, wave age, local water depth, and swell condition are described. Physical interpretation is offered on the relationship between SWH and DSW through the surface wave orbital velocity. Among the various environmental factors, the swell exerts the largest influence on the resulting relationship between DSW and SWH. The analysis considers a stationary transmitter and receiver only in order to provide insight into the impact of wave motions on the Doppler signatures.

Radiometric and radar data from NASA’s Soil Moisture Active Passive (SMAP) satellite are presented in a study of the Ross Ice Shelf, Antarctica. L-band brightness temperature (TB) patterns compare favorably to the outflow patterns from East and West Antarctica. CoolerTBis associated with the broad outflow from West Antarctic ice streams and the outflow from narrow outlet glaciers that drain East Antarctica. Aside from outlet glacier discharges, ice from East Antarctica is thinner and radiometrically warmer than that from West Antarctica.TBis stable across the ice shelf over the 6-year period of observations (1-2 K standard deviation). Over shorter times, surface melt events cause pre- and post-meltTBto vary by as much as 5 K in vertical polarization. Radar measurements highlight areas where backscatter is strong from melt related ice lenses and ice layers, consistent with a corresponding decrease inTB. TheTBpolarization ratio on the ice shelf is approximately 1.13 and decreases from the West Antarctic grounding line towards the East Antarctic outlet glaciers. The backscatter polarization ratio increases by several dB from West to East Antarctica, indicating a decreasing influence of volume scatter toward East Antarctica. The decreasingTBpolarization ratio indicates a diminishing role of firn layering on the depth-integrated emission. There is a negative correlation between warming brightness temperature and thinning. An explanation for this observation is that the relatively warm ice shelf has a relatively shallow (500 m or less) penetration depth leading to a warm physical temperature bias.

Ice sheet subsurface temperature is important for understanding glacier dynamics, yet existing methods to obtain the temperature of the ice sheet column are limited toin situsources at present. The ultrawideband software-defined microwave radiometer (UWBRAD) has been developed to investigate the remote sensing of ice sheet internal temperatures. UWBRAD measures brightness temperature spectra from 0.5 to 2 GHz using 12 subchannels and employs a sophisticated algorithm for detection and mitigation of radio frequency interference (RFI). The instrument was deployed during a flight over northwestern Greenland in September 2017 and acquired the first wideband low-frequency brightness temperature spectra over the ice sheet and coastal regions. The results reveal strong spatial and spectral variations that correlate well with internal ice sheet temperature information. In this article, the section of the flight path ranging from the Camp Century to NEEM to NGRIP boreholes is used for subsurface temperature estimation. A “partially coherent” forward model is applied along with a Robin model for the temperature profile and a two-scale model of ice sheet density variations to describe measured brightness temperatures. Using this model, vertical temperature profiles are retrieved along the flight path using a sequential Bayesian estimator; borehole measurements at the three campsites are used to obtain Bayesian priors. The retrieved temperature profiles show reasonable behaviors and demonstrate the potential of ultrawideband microwave radiometry for remotely sensing internal ice sheet temperatures.

Wideband radiometers must contend with a challenging RFI environment and with frequency-dependent reflections between receiver components caused by impedance mismatches. Channelizing the bandwidth prior to amplification can prevent strong interference in one portion of bandwidth from corrupting all of the data and can allow for the incorporation of isolators to reduce reflection effects, but the additional components required cause additional losses, reducing the sensitivity of the radiometer. Avoiding channelization in the radiometer front end reduces these losses, but increases the potential impact of reflections and high amplitude RFI sources. This paper investigates tradeoffs between “channel-ized” and “non-channelized” architectures for the proposed PolarRad 0.5-2 GHz microwave radiometer.

The Soil Moisture Active/Passive satellite was launched in 2015 to provide global and continuous maps of land surface soil moisture and freeze-thaw using L-Band microwave radiometry. Even though the 1400-1427 MHz frequency used by SMAP is a protected portion of the spectrum, Radio Frequency Interference (RFI) is still observed that can corrupt the radiometer's measurements. Nine distinct algorithms are implemented as part of SMAP's level 1 processing to detect and filter out RFI contributions. However, any remaining undetected RFI are major concern especially at the locations of cal/val sites used for evaluating soil moisture retrieval performance. This paper presents an analysis of the RFI environment at SMAP cal/val site locations and assesses the impact of RFI on soil moisture retrievals at those locations.

Analyses of GNSS-R data sets have revealed the occasional presence of coherent signals over land areas. Studies have been conducted of modeling such returns using classical scattering theories that consider the geometry, the frequency band, and surface parameters as inputs. The surface roughness is a crucial parameter that is not widely available from ancillary sources. This paper presents a comparison of roughness statistics derived from Digital Elevation Maps (DEMs) having different spatial resolutions, and shows the importance of having a high-resolution DEM in order to resolve small scale roughness. This is particularly important when modeling reflected signals over very flat surfaces where coherency can be significant.

Accurately measuring the vertical temperature profiles of ice sheets and glaciers can provide critical data for numerical ice sheet models used in global sea level projections. Ice-penetrating radars and radiometers have been utilized independently in remote sensing campaigns to measure englacial ice temperatures. Here we show that by combining these two instruments, which have complimentary sensitivities to lower and upper depths of the ice column, respectively, the overall uncertainty in temperature profile retrievals can be significantly reduced. We present unified simulations of radar attenuation and radiometer brightness temperature as functions of depth and frequency to demonstrate the value in this combined active/passive remote sensing approach.

A comparison of three different electromagnetic scattering models for delay-Doppler maps (DDMs) of global navigation satellite system reflectometry (GNSS-R) from land is performed along a Cyclone Global Navigation Satellite System (CYGNSS) track over a validation site in the San Luis Valley, Colorado, USA. The peak reflectivity profiles of all three models and of the corresponding CYGNSS data are found to be in general agreement and are strongly influenced by topography. An intercomparison of DDM structure for one acquisition is also included. Efforts to refine the model results using a high resolution lidar survey are ongoing.

Sea ice thickness and salinity are important quantities in understanding and forecasting the evolution of the cryosphere. However, the retrieval of multiple sea ice parameters through microwave remote sensing is a challenging task. In this study, the potential advantages of using a multi-channel wideband microwave radiometer are demonstrated through simulations of the retrieval of both sea ice thickness and salinity for multiple ice types and for different numbers of radiometer channels.

S-band observations from NASA's Passive/Active L/S Band (PALS) radar from the SMEX02 campaign were used to estimate soil moisture. The “alpha” method is applied for this process, in which a time series of ratios of normalized radar cross section values at successive measurements is used to infer the corresponding soil moisture time series given ancillary information on the minimum and maximum soil moisture values expected over the time series. Results are examined as a function of the polarization and crop type. The results show reasonable retrieval performance, indicating the potential of using S-band observations from the future NASA/ISRO SAR (NISAR) mission.

The NASA ISRO Synthetic Aperture Radar (NISAR) mission is currently under development and is scheduled for launch in 2022. The NISAR mission will provide global data sets of Earth land surface dynamics that are critical for multiple Earth Science disciplines including observations of ecosystem carbon and water cycles. Global L-band radar observations at high spatial resolution will be helpful for soil moisture applications. One of the goals of the NISAR mission is to provide a global soil moisture product at 200 m resolution with a global revisit frequency of 6 days. A time-series ratio algorithm was implemented using NISAR simulated SMAPVEX12 UAVSAR data, which is an L-band airborne radar backscatter measurement. For a NISAR-like configuration, backscatter at incidence angles from 30 to 50 degrees was considered in this study. The initial retrieval statistics following comparisons with in-situ ground truth show correlation coefficients (R) to be about 0.81, and the unbiased RMSE to be about 0.06 m3/m3. Results from dual co-polarization and/or cross-polarization modes were evaluated and considered for performance improvement.

This paper presents a study of snowpack thermal emissions at long wavelengths and over a wide frequency band. Brightness temperature measurements of a snow layer are reported and used to estimate the travel time through the layer. The Ultra-Wideband Software-Defined Radiometer (UWBRAD) and the Wideband Autocorrelation Radiometer (WiBAR) were deployed at the Keweenaw Research Center (KRC) from February to April 2020 to demonstrate these techniques. Results on snowpack brightness temperature and thickness measurements are presented and discussed.

Vertical ice sheet temperature profiles are affected by processes such as snow accumulation rates, geothermal effects, the properties of the ground over which the ice column is sitting. These internal ice sheet temperatures and their variations both with depth and location are crucial in understanding ice sheet evolution. The temperature profile in depth plays an important role in influencing stress-strain relationships in the ice sheet volume, and therefore impacts ice sheet dynamics including deformation and flow across the ice sheet base. There are currently no instruments for remote sensing the entire vertical ice sheet temperature profile. Most current information about the depth and spatial variation in ice sheet temperatures comes from borehole measurements [1].

This work demonstrates the creation of dynamic inland water body masks at spatial resolutions ranging from 1 to 3 km through the use of a recently developed coherence detector for the delay-Doppler maps produced by the cyclone global navigation satellite system (CYGNSS) constellation. The use of the coherence of the observed measurements reduces many of the uncertainties associated with previous signal-to-noise ratio-based water body detection approaches for CYGNSS. Using data from January 2018 to February 2020 and producing maps representing time intervals ranging from 3 months to 2 years, the water body masks created are found to be associated with a probability of detection that exceeds 80% as compared to the Pekel water mask developed from Landsat observations. The analysis presented in this work highlights the potential of using spaceborne Global Navigation Satellite Systems Reflectometry (GNSS-R) systems for dynamic inland water body mapping.

An algorithm for detecting coherence in Cyclone Global Navigation Satellite System (CYGNSS) mission delay-Doppler maps (DDMs) is presented. Because CYGNSS DDMs report only the observed power without phase information, the algorithm uses estimates of power “spread” within the DDM to flag coherency. Since the estimate used is a ratio of the powers in differing portions of the DDM, it is less sensitive to absolute power calibration and to the GPS C/A code type observed, and is applied to CYGNSS Level-1 uncalibrated DDMs. The basic detector formulation is described along with modifications to improve performance in lower signal-to-noise ratio (SNR) situations. The required detection thresholds are determined using matchups with CYGNSS “Raw I/F” mode measurements for which the DDM phase can be computed and used to identify coherence more precisely. Application of the final detector over a large CYGNSS data set suggests that approximately 8.9% of all inland returns are coherent. Inland regions persistently identified as coherent were found largely to be associated with the presence of water bodies. A smaller set of desert locations apparently having very low surface roughness were also found to be associated with persistent coherence. The detector was also applied to a set of ocean measurements, with the results showing that persistent coherence is limited to areas with sheltered waters. Ocean tests avoiding such regions indicate that the detector's false-alarm rate is approximately 0.0012% for the detection threshold used.

Electromagnetic scattering and emission from 1-D rough surfaces with multiple elevations are studied using full-wave simulations. Both the root-mean-square (rms) heights and the surface length are large compared to the wavelength. A novel multilevel steepest decent-sparse matrix canonical grid (MLSD-SMCG) method is proposed to address limitations in the original SMCG. The uniform Nystrom method and neighborhood impedance boundary condition (NIBC) are also incorporated in solving the dual surface integral equations (SIEs) of the method of moments (MoM). Simulation results are illustrated at L-band for soil and ocean surfaces. The surface rms heights and lengths are up to 1.43 and 243.8 m corresponding to 6 and 1024 wavelengths at 1.26 GHz, respectively. For ocean surfaces, the wind speeds up to 20 m/s are considered, and the entire spectrum is included to capture all relevant surface length scales. Numerical results indicate the proposed approach is computationally efficient and accurate. Energy conservation checks in simulations are at $10^{-4}$ for ocean scattering and emission. Also, the effects of wind-driven roughness on ocean emissivity are further investigated using the proposed approach in terms of wind speed and observation angle for both polarizations.

The Ultra-Wideband Software Defined Microwave Radiometer (UWBRAD) is a wideband radiometer operating from 0.5 to 2 GHz for remote sensing of polar ice sheet temperature profiles. Small-scale (cm to m) fluctuations in firn density in the upper portion of the ice sheet significantly impact observed brightness temperatures. Previously, a fully coherent model based on solving Maxwell’s equations for thousands of layers throughout the entire ice sheet was developed. Density profiles in the model are described as the sum of a smooth average density profile with a spatially correlated random process that represents density fluctuations. In this article, we develop a “partially coherent” implementation of the coherent model that captures the impact of variations in ice density on predicted brightness temperatures while improving computational efficiency. The partially coherent model divides the ice sheet into blocks. Within each block, the coherent model is applied to take into account coherence among the contributions of closely spaced layers. A Monte Carlo procedure is used to calculate the average block reflection and transmission parameters. Between adjacent blocks, interactions are assumed to be incoherent, and the radiative transfer theory is used to incoherently cascade block parameters. Results of the partially coherent model are in good agreement with the fully coherent model and also with Soil Moisture Ocean Salinity (SMOS) and UWBRAD brightness temperature observations.

Advances in RFI detection and filtering have promoted the design of wide-bandwidth radiometers that operate outside the traditional protected radiometry bands. Wideband operation requires the use of components without well-matched impedances, producing multiple reflections within a system that may impact the calibration process. Operating over large bandwidths also exposes the system to unknown and possibly high power RF signals that can damage components, requiring the use of protective devices that can increase loss and reflections further. UWBRAD is an ultrawideband radiometer designed to operate from 500-2000 MHz that has successfully flown three missions to the polar regions of Earth (Greenland and Antarctica). This paper reviews the calibration methods, challenges, and RFI environments encountered in these missions with consequences and lessons for future wideband radiometers.

NASA's CYclone Global Navigation Satellite System (CYGNSS) mission operates a constellation of 8 small satellites that provide ocean wind speed measurements with dense spatial coverage and a median revisit time of about 4 hours. This paper investigates the possibility of using the “rapid revisit” characteristics of CYGNSS measurements to create a detector of convective activity by examining the variability of CYGNSS wind speeds over small intervals in space and time.

The National Aeronautics and Space Administration (NASA) - Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) is being developed in order to provide highly spatial resolution L- and S-band backscatter observations of the Earth's surface. Remotely sensed soil moisture is one of NISAR applications of interest. This paper reports an initial analysis of the possibility of using NISAR modes to retrieve soil moisture based on two different methods: a snapshot method and the time series technique. Preliminary results of the forward modeling of the backscattered signal over land and the soil moisture retrievals are presented for bare surfaces.

In February 2019 a Project Authorization Request was approved by the Institute of Electrical and Electronics Engineers (IEEE) Standards Association with the title “Standard for Global Navigation Satellite System Reflectometry (GNSS-R) Data and Metadata Content”. A Working Group has been assembled to draft this standard with the purpose of unifying and documenting GNSS-R measurements, calibration procedures, and product level definitions. The Working Group (http://www.grss-ieee.org/community/technical-committees/standards-or-earth-observations/) includes members, collaborators, and contributors from academia, international space agencies, and private industry. In a recent face-to-face meeting held during the ARSI+KEO 2019 Conference, the need was recognized to develop a standard with a wide range of operations, providing procedure guidelines independently of constraints imposed by current limitations on geophysical parameters retrieval algorithms. As such, this effort aims to establish the fundamentals of a potential virtual network of satellites providing inter-comparable data to the scientific community.

A method for adaptively determining a desirable coherent integration time for radar observations of a moving clutter target is examined. A signal model appropriate for such measurements is first defined, along with an approach for estimating the coherence time from measured data. This coherence time estimate is then used as the coherent integration time in a reprocessing of the measured data. Simulations are shown that illustrate the potential advantages of this approach in reducing the variance of the clutter power estimate, particularly at low clutter to noise ratios, as compared to a purely incoherent integration. However the initial correlation time estimator examined is found to be ineffective, so that alternate strategies are required to obtain the desired performance improvements.

An ultra-wideband radiometer was built and deployed in the Arctic to monitor the microwave emissions of sea ice from a stationary platform on an ice floe. The experiment was performed as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the far north of the Laptev Sea. Brightness temperature data were acquired over the spectrum 0.5-2 GHz during the first phase of the expedition. The outcome of the experiment is expected to provide new insights into the advantages of wideband radiometry for the remote sensing of Arctic sea ice properties.

Microwave measurements have been previously used to detect melt events due to their sensitivity to the presence of liquid water in snow. Since NASA's SMAP mission offers a valuable set of low frequency radiometer measurements, SMAP measurements have been used as a tool to detect melt events. SMAP's L-band radiometer also covers virtually the entire Greenland ice sheet twice daily. The overpasses center on morning and evening hours as the satellite is on a 6AM/6PM equator-crossing orbit, and the spatial resolution of the instrument is about 40 km. In this paper, the response of L-band measurements to surface melting of the ice sheet from 2015 through 2019 melt seasons is investigated. It is shown that the Greenland ice sheet experienced an unusually strong melt event at the end of July 2019, which extended the melt area across much of dry snow zone of the ice sheet over a period of two days.

The Global Navigation Satellite System reflectometry (GNSS-R) community has traditionally used the Kirchhoff approximation to model how the coherent reflected power reduces as a function of the RMS height of the rough surface observed. While this approximation has been valid for most GNSS-R applications to date, the community has recently raised the question of the model's validity when the normalized coherent reflected power is very low ( ≤ -20dB) due to increased interest in measuring the coherent reflected power in situations where the incoherent reflected power is dominant. To investigate the trend of the normalized coherent reflected power below -20dB, Monte Carlo simulations were performed by randomly generating Gaussian rough PEC surfaces with various RMS heights and averaging over multiple realizations at each RMS height to obtain a reflected power whose incoherent component has been averaged out, leaving only the coherent reflected power behind. In this process, the statistics of the Rician random variable obtained when coherent specular scattering from a rough surface is measured must also be considered, and it can be shown that the accuracy of the coherent power estimate is dependent on the number of realizations used and the ratio of the coherent and incoherent powers. This analysis also shows that a large number of averages can be required to obtain reasonable accuracy in estimating the coherent power in the limit of low coherent to incoherent power ratio.

The Cyclone Global Navigation Satellite System (CYGNSS) measures GPS signals specularly reflected from Earth's surface to remotely sense ocean surface roughness and wind speed. The mean square slope (mss) is a key physical parameter that relates the ocean surface properties (wave spectra) with the CYGNSS measurement of the normalized bistatic radar cross section (NBRCS). An approach to model the mss for validation with CYGNSS mss data was developed by adding the contribution of a high frequency tail to the IFREMER WAVEWATCH III (WW3) mss. It is demonstrated that the ratio of CYGNSS mss and the modified WW3 mss can be used to diagnose potential calibration errors that exist in the Level 1 calibration algorithm. This approach can help to improve CYGNSS data quality, including the Level 1 NBRCS and Level 2 ocean surface wind speed and roughness.

This letter analyzes the background signals and thermal noise received over ocean scenes in spaceborne global navigation satellite system (GNSS)-reflectometry (GNSS-R) remote sensing using observations from the cyclone GNSS (CYGNSS) constellation. The measured noise floor contains a stable and predictable radiometric thermal noise component and a more variable background signal component from unintended specular reflections within the CYGNSS receive antenna pattern from all GNSS satellite constellations (GPS, Galileo, GLONASS, Beidou, and all SBAS). The presence of SBAS reflections, in particular, is evident in the noise floor measurements, especially the U.S. wide area augmentation system (WAAS) satellites. The results show that the impact is negligible, since background signal contributions by other GNSS transmitters affect both the “signal” and “noise” portions of CYGNSS's delay Doppler map measurements, and therefore cancel when the measured noise floor is subtracted from the desired signal. The potential increase in measurement uncertainty introduced by any residual background signal to the CYGNSS calibration is analyzed.

This paper demonstrates how the fully adaptive radar framework can be applied to cloud profiling radars. A simulation based on the GEOS5 nature run dataset is introduced in which the cloud profiling radar continuously adapts its pulse repetition frequency (PRF) such that the unambiguous range is 1.2 times the cloud column height. This process maximizes the (PRF) which would in turn maximize the unambiguous velocity estimate.

Collaborative networks of small satellites will form future Earth-observing systems. Maximizing the science value of measurements from such systems will require autonomous decision making with regard to management of limited resources (i.e. power, communications, and sensor configuration). The complexity of this decision space warrants the creation of software tools to aid users in efficient modeling and simulation of collaborative remote sensing networks. In this paper, we present a new open-source software library and tool-set that has been specifically designed for simulating such networks. Details of the object-oriented C++ library are presented with results from example simulations to confirm that it is able to address this challenge. The software tools developed offer enhanced simulation capabilities to developers of future observing system simulation experiments (OSSEs) with collaborative networks of adaptive sensor platforms.

The concept of wideband autocorrelation radiometry has recently been proposed and applied for the remote sensing of snow and lake ice. Such instruments measure the microwave emission from a scene of snow and ice over a wide and low frequency band where volume scattering within the snow/ice layer is negligible. Experiments have demonstrated that such wideband brightness temperature spectra can show oscillatory features. These features arise from coherent interference among the direct upward emission and its replicas from multiple reflections, are related to the layer thickness of snow or ice, and can be affected by interface roughness or any above snow vegetation canopy. The latter is therefore an important factor affecting the application of wideband autocorrelation radiometry in terrestrial snow remote sensing. In this paper, we analyze the effects of an above snow vegetation layer on brightness temperature spectra, particularly the possible decay of wave coherence arising from volume scattering in the vegetation canopy. In our analysis, the snow layer is assumed to be flat, and its upward emission and surface reflectivities are modeled by a fully coherent model, while the volume scattering from the vegetation layer is described by an incoherent radiative transfer model. The solution to the radiative transfer equation is obtained through an interative approach accounting for multiple scattering effects. The angular and polarization coupling arising from volume scattering and the emission contributed by the vegetation layer all cause smoothing of oscillatory patterns in the observed brightness temperature spectra.

The Cyclone Global Navigation Satellite System (CYGNSS) mission employs measurements of the quasi-specular forward scattering cross section of the ocean surface for retrieving sea surface wind speed and roughness globally and, particularly, in the inner core of tropical cyclones. CYGNSS Level 2 data products include the ocean surface wind speed U10and the mean square slope (MSS). An "excess MSS" approach has been previously proposed to account for sea state condition effects, including the presence of non-local swell and the degree of wave development, to reduce the influence of these effects and thereby improve wind speed retrievals. The approach requires ancillary information on the sea surface MSS and wind speed from models, and has been shown to provide some improvement in wind speed retrievals. In this work, the inclusion of an additional parameter, the inverse wave age, is examined to determine if additional improvements can be achieved. MSS and inverse wave age information is obtained from the WaveWatch III model run by IFREMER, and is used to compute a feedback signal for a closed-loop retrieval algorithm for both wind speed and MSS. The goal of the effort is to improve further the accuracy of CYGNSS Level 2 wind speed retrievals, and also to provide additional wave information if possible. This paper also investigates the technical methodology and potential benefits of integrating CYGNSS observations into the WW3 model.

In this paper, physical models for ocean surface swell effects on L-band backscatter at 40° incidence angle are used to interpret measurements from NASA's Soil Moisture Active/Passive (SMAP) radar. The backscatter normalized radar cross section (NRCS) of the ocean surface is predicted using the two-scale (or composite surface) model (TSM). The wind-driven ocean surface in the model is characterized using the Durden-Vesecky directional spectrum, while swell effects are represented through their contribution to the long wave slope variance. The excess slope variance attributed to swell is then obtained from the Wave Watch III wave model. Preliminary comparisons in HH polarization show an improved agreement between modeled and observed NRCS data when swell effects are included.

Due to solar heating, many geophysical quantities, such as precipitation, sea surface temperature, and wind, have distinct diurnal signatures in the tropical region. To explore the potential of wind speed measurements of the Cyclone Global Navigation Satellite System (CYGNSS) mission launched in December 2016, we examine the degree to which wind diurnal cycles can be estimated from the surface wind speed data provided by CYGNSS along with data from the ASCAT mission. Ocean wind speed measurements are simulated based on the Cross-Calibrated Multi-Platform analysis fields of surface wind vectors. We estimate the amplitude and phase of diurnal wind speed based on a discrete Fourier transform generalized to analyze unevenly sampled time series of wind speed anomalies. The results show that the combination of CYGNSS and ASCAT measurements can provide some ability to observe diurnal wind information, but that additional time samples (e.g., from other measurement sources) would likely provide further benefits in estimation performance.

Time-series retrievals of soil moisture obtained from the Cyclone Global Navigation Satellite System (CYGNSS) constellation are presented. The retrieval approach assumes that vegetation and roughness changes occur on timescales longer than those associated with soil moisture changes to allow soil moisture sensing in the presence of vegetation and surface roughness contributions as well as the varying incidence angles associated with spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) systems. The approach is focused on incoherent scattering from land surfaces due to the expectation that coherent land surface returns arise primarily from inland water body contributions that are not directly representative of soil moisture. An approach for discarding coherent CYGNSS measurements is therefore developed and described. Because the approach requires the retrieval of N temporal soil moisture samples at a given location but uses only N-1 ratios of CYGNSS measured quantities, ancillary information is incorporated in the retrieval through the use of maximum and minimum monthly soil moisture maps obtained from the Soil Moisture Active Passive (SMAP) mission. Retrieved soil moistures are presented for the 6-month period December 2017-May 2018 and are compared against values reported by the SMAP mission. The comparisons suggest that there exists the potential for using spaceborne GNSS-R systems for global soil moisture retrievals with an rms error on the order of 0.04 cm3/cm3over varied terrain.

An analysis of the coherency properties of specular scattering from ocean and land surfaces as observed in global navigation satellite system-reflectometry (GNSS-R) and signals of opportunity systems is presented. This analysis applies existing approximate models for the coherent and incoherent contributions. Approximate expressions are developed for when one component of the return is likely to dominate as a function of surface and observing system properties. The model developed is then applied for sea surface returns, and the relative contribution of the coherent term is expressed as a function of the receiver height, frequency, incidence angle, and wind speed. For L-band spaceborne measurements, it is shown that coherence is expected only for wind speeds less than 2-3 m/s, while for P-band spaceborne measurements, coherence can dominate returns for wind speeds up to 5-7 m/s. For land surface measurements from space, it is shown that the surface rms height needs to be sufficiently low for coherent components to dominate returns. Coherence dominates for roughness values not exceeding a range of 5-7 cm for the L-band and 15-30 cm for the P-band. For the L-band, these conditions over land are likely to be created primarily by inland water bodies. A model for the specular scattering from a water body, including earth curvature effects, is then developed to highlight the strong dependence of the resulting coherent field on the shape of the water body and any offset in its location from the specular point. These results further clarify the significant variability that should be expected in coherent scattering from inland water bodies.

An ultrawideband radiometer was used to measure microwave brightness temperature spectra over Arctic sea ice in the Lincoln Sea near the north coast of Greenland. Spectra over the range of 0.5-2 GHz were compared to thermal infrared images collected during the airborne campaign and also compared to nearly concurrent Sentinel-1 C-band synthetic aperture radar (SAR) data. Based on those comparisons, spectral signatures were associated with thick multiyear ice and thin ice. A radiative transfer (RT) model consisting of a homogeneous slab of sea ice bounded by sea water and air was then used to invert the spectra for sea ice thickness and salinity. Inferred thicknesses were consistent with ice thickness climatology for ice floes in the Lincoln Sea. Salinities are higher than expected which may be a consequence of neglecting surface and volume scattering contributions in the models.

The demand for microwave spectrum for commercial and industrial use has been increasing rapidly over the last decade, putting stress on the limited spectral resources for passive microwave remote sensing. Radio frequency interference from man-made sources is expected to become worse over the coming years. At 1.4 GHz, the SMAP mission has implemented and demonstrated advanced interference detection algorithms for its microwave radiometer. This scheme will not be feasible at higher microwave frequencies (above 6 GHz) due to much larger radiometer bandwidths used and the limited downlink data volume available to implement RFI filtering algorithms in the ground processing. In this paper, we present the design, development, and test of an advanced on-board interference detection and RFI filtering digital back-end that is capable of operation for a 1 GHz-radiometer bandwidth. We describe the combined RFI detection algorithms implemented in the digital backend's firmware and the on-board RFI filtering of interference-corrupted data that will be necessary to limit downlink rate requirements for future high-frequency microwave missions.

Soil moisture plays a pivotal role in a wide range of hydrological and geophysical processes. The ability to estimate soil moisture is key to improved characterization of precipitation cycles, soil erosion as well as weather forecasts. However, world-wide in situ monitoring of soil moisture is impractical thus necessitating the need for its remote sensing. Sensitivity to land surface properties using Global Navigation Satellite System Reflectometry (GNSS-R) is well documented suggesting potential use for soil moisture retrieval. This study will attempt to elucidate the physical mechanisms through which GNSS land surface returns will exhibit dependence on soil moisture levels. Furthermore, it will describe a simulation study through which land surface returns, namely the specular Normalized Radar Cross-Section (NRCS), will be modelled and a time series retrieval approach demonstrated through which soil moisture may be derived. Particular emphasis is placed on complications due to surface roughness, land cover, and angle effects.

This paper studies the amplitude distribution of bistatic sea clutter using a physics-based model. Such a study assists in understanding clutter statistics for target detection and remote sensing applications. The formulation of the model is based on a “two-scale” decomposition and Elfouhaily spectrum. This model provides a physical basis of the mean power (texture) function in the compound Gaussian model. The model developed in this paper does not include sea surface features such as breaking waves, so that the “sea spike” behaviors of sea clutter important at lower grazing angles are not captured. The model is therefore limited to application at larger grazing angles but otherwise throughout the entire bistatic scattering hemisphere.

The objective of this study is to cross-compare three algorithms for retrieving surface soil moisture (SSM) from ESA's Sentinel-1 (S-1) data. The context is provided by the large scientific and application interest in SSM products at high resolution and regional/continental scale that can be retrieved from S-l data alone or in combination with other missions such as NASA/SMAP and ESA/SMOS. Of the three investigated algorithms, one inverts a scattering model exploiting a Bayesian approach, whereas the other two are change detection approaches. The cross-comparison is carried out by using both simulated and experimental data. Strengths and weaknesses of the three algorithms are identified and discussed.

The Soil Moisture Active/Passive satellite microwave radiometer has been providing measurements of L-band thermal emission from Earth for more than 2 years. SMAP retrieves surface soil moisture from its brightness temperature measurements, and continues to provide science products to the user community. Even though the SMAP radiometer operates in a protected band, its measurements are still corrupted by Radio Frequency Interference (RFI) caused by illegal in-band transmissions or out-of-band emissions. The SMAP radiometer was designed to include special hardware to enable RFI detection and filtering using multiple detection algorithms. Given the good overall performance of SMAP algorithms to detect RFI sources, an automatic tool to report source properties automatically was developed and is now operational. This paper provides a preliminary analysis of the outputs of this reporting tool with a particular focus on the evolution of the RFI environment observed by SMAP during its period of operations.

Since July 2015, the radar receiver aboard the SMAP satellite has been operating in a “receive only” mode from which GNSS-R measurements can be produced. SMAP's high-gain antenna with high cross-polarization isolation offers a unique opportunity to study Earth remote sensing with GNSS-R. These data recently been used to produce some of the first spaceborne polarimetric GNSS-R measurements. Previous work has shown the properties of the relative amplitudes of the received H - and V -polarized signal components; however, the fully coherent, multi-channel receive data from SMAP offers an opportunity to examine other polarimetric properties, such as the LR and RR components (of interest to future mission designs), complex cross-correlations between components (ie. HRVR or LRRR), and their relative magnitudes and phases. This paper presents initial results of an investigation of the new information in SMAP's dual-polarized GPS L2C reflection measurements over different land types.

The Ultra- Wideband Software Defined Microwave Radiometer (UWBRAD) was developed at The Ohio State University to provide nadiral brightness temperatures measurements of ice sheets primarily but also other geophysical media in the spectral range 0.5-2 GHz. During its deployment in Greenland in September 2017, UWBRAD acquired data over the ice sheets but also over open ocean. This paper focuses on the analysis of these ocean datasets in order to show the potential of using 0.5-2 GHz microwave radiometry to retrieve sea surface salinity.

The Ultra-Wideband Software Defined Microwave Radiometer (UWBRAD) measures scene brightness temperatures from 0.5-2 GHz. UWBRAD was deployed in a September 2017 airborne campaign in Greenland, and observed brightness temperatures of the ice sheet as well as sea ice, the ocean surface, and land regions during the transit to and from Calgary, Canada (the aircraft base of operations). This presentation will review the campaign and datasets collected. Spectral features of thermal emissions from the ice sheet and other geophysical regions are also examined to obtain insight into the utility of 0.5-2 GHz thermal emission measurements for remote sensing applications.

Earth's cold regions are key elements of the planet's climate system: they have strong feedbacks with global change and they have a direct impact on human activities. Despite their importance, at present they are not adequately monitored by state-of-the-art instruments. In order to fill this gap, a dedicated spaceborne mission called Cryorad has been proposed in the framework of the ESA Earth Explorer 10 call. The mission would comprise a 0.4-2 GHz nadir-looking radiometer installed on a polar-orbit satellite. Scientific and technical studies are underway, as well as experimental campaigns in Greenland and Antarctica.

Soil moisture content is an essential climate variable that is operationally delivered at low resolution (e.g. 36-9 km) by earth observation missions, such as ESA/SMOS, NASA/SMAP and EUMETSAT/ASCAT. However numerous land applications would benefit from the availability of soil moisture maps at higher resolution. For this reason, there is a large research effort to develop soil moisture products at higher resolution using, for instance, data acquired by the new ESA's Sentinel missions. The objective of this study is twofold. First, it presents the validation status of a pre-operational soil moisture product derived from Sentinel-1 at 1 km resolution. Second, it assesses the possibility of integrating Sentinel-2 data and additional ancillary information, such as parcel borders and high resolution soil texture maps, in order to obtain soil moisture maps at “field scale” resolution, i.e. ~0.1 km. Case studies concerning agricultural sites located in Europe are presented.

The CubeSat Radiometer Radio Frequency Interference Technology Validation (CubeRRT) mission is developing a 6U CubeSat system to demonstrate radio frequency interference (RFI) detection and filtering technologies for future microwave radiometer remote sensing missions. CubeRRT will perform observations of Earth brightness temperatures from 6-40 GHz using a 1 GHz bandwidth tuned channel and will demonstrate on-board real-time RFI processing. The system is currently under development, with an expected launch date in mid-2018 followed by a one year period of on-orbit operations. CubeRRT spacecraft and radiometer instrument testing as well as the mission concept of operations are described in this paper.

In this paper we discuss the necessary technology required to enable the future of spectrum resource constrained missions. We discuss the CubeSat Radiometer Radio Frequency Interference Technology (CubeRRT) validation mission and the development of its digital backend, necessary for performing on-board RFI detection and filtering for wideband high frequency radiometry. The CubeRRT mission will validate the on-board RFI filtering technology solving technological challenges such as bandwidth, data downlink volume, and RFI types. We present a few initial results of the backend spectrometer leading to full-system integration and test.

Future observing systems simulation experiments (OSSEs) will need to be of increased sophistication to support emerging sensors that exploit parametric adaption, resource management in constrained environments, and the collaboration of distributed sensing nodes. This paper demonstrates the power of using adaptive approaches to remote sensing through a fully adaptive radar imaging example that uses experimental data. In the demonstration, the image resolution varies between 0.47 m and 1.2 m leading to a cost metric savings of 18% and 22% compared to fixed coarse and fine resolution tests. The experimental demonstration is used to inform a discussion of how future OSSEs will need to operate.

The measurements made by the Soil Moisture Active/Passive (SMAP) mission are affected by the presence of Radio Frequency Interference (RFI) in the protected 1400-1427 MHz band. In SMAP data processing, the main protection against RFI is a sophisticated RFI detection algorithm which flags sub-samples in time and frequency that are contaminated by RFI and removes them before estimating the brightness temperature. This contribution presents two additional approaches that have been developed to address the RFI concern in SMAP. The first consists in locating sources of RFI, which can then be reported; once located, it becomes possible to report RFI sources to spectrum management authorities, which can lead to less RFI being experienced by SMAP in the future. The second is an additional RFI detection method that is based on detecting outliers in the spatial distribution of measured antenna temperatures.

The Level 2 data product of the Cyclone Global Navigation Satellite System (CYGNSS) mission includes the retrieved ocean surface wind speed and the mean square slope (MSS), which are derived from the Level 1 normalized bistatic radar cross section (NBRCS). In the current L2 retrieval algorithm, the wind speed is retrieved using empirical geophysical model functions (GMFs) based on matchups with ground truth wind speed. However, sea state conditions, including the presence of external swell and the degree of wave development, complicate the ocean surface wave spectra and increase the uncertainty of the wind speed retrieval. An excess MSS approach is proposed to model sea state conditions. It calculates the excess MSS responsible for the sea state condition effects using ancillary data and the Elfouhaily et al. wave spectral model. A case study demonstrates that this approach reduces the wave effect (due to the sea state condition) on the CYGNSS NBRCS and improves the L2 wind speed retrieval.

Cross-polarized backscatter normalized radar cross section (NRCS) measurements have been of increasing interest due to their potential to improve wind speed retrievals at high wind speeds. The development of physics-based forward models for cross-polarized backscatter has been challenging due to the higher-order scattering mechanisms that contribute to this quantity. In this paper, predictions of the two-scale model (TSM) and the small slope approximation (SSA2) for cross polarized backscatter are examined to obtain insight into their relative merits. A recently introduced high frequency (HF) approximation for cross polarized backscatter under the SSA2 is also examined and compared to a similar approximation based on the TSM. The results provide guidance for the continued development of forward models for sea surface remote sensing using cross polarized backscatter.

The ultrawideband software-defined microwave radiometer is a 500–2000-MHz radiometer developed to probe temperatures inside ice sheets. Given the instrument’s operation outside of protected portions of the spectrum, radio frequency interference (RFI) is a significant concern, and the instrument is designed to facilitate RFI detection and filtering. This paper analyzes the design and operation of the radiometer, the accuracy and stability of the brightness temperatures it produces, and the RFI analyses of the results acquired in its debut flight over northern Canada and Greenland in September 2016.

An ultra-wideband radiometer has been developed to measure subsurface properties of the cryosphere including ice sheets and sea ice. The radiometer measures brightness temperature spectra from 0.5 to 2 GHz using 12 channels, each of which measures scene brightness temperatures over an ~88-MHz bandwidth resolved into 0.24-MHz intervals. The instrument was flown over northwestern Greenland in September 2016 and acquired the first, wideband, low-frequency brightness temperature spectra over the ice sheet and coastal region. The results reveal strong spatial and spectral variations that correlate well with the physical properties of the surface encountered along the flight path, which started over ocean, then passed the rock near the coast, and then up onto the ablation, wet, percolation, and dry snow zones of the interior ice sheet. In particular, strong spectral responses in percolation and dry snow zones are observed and plausibly explained by varying the distribution of horizontal density layers and isolated icy bodies in the upper portion of the firn. The success of the airborne deployment of the instrument and subsequent implementation of algorithms to limit radio frequency interference in unprotected bands is motivating continued airborne investigations as well as stimulating research into the feasibility of a spaceborne instrument.

The Soil Moisture Active/Passive (SMAP) satellite mission measures Earth's radiation in the protected portion of the spectrum at 1.413 GHz (L-band) to retrieve geophysical quantities of the surface, such as soil moisture and the frozen/thawed state of the soil. The presence of radio-frequency interference (RFI) in this band is significant and impacts the quality of SMAP measurements. Knowing the location of the sources of RFI is important, because it can help to identify the source itself and also be used to develop strategies to mitigate its impact of the RFI on the data. This paper presents an algorithm that takes advantage of the viewing geometry of SMAP to locate sources of RFI. The results are validated using known locations of RFI sources and by comparison with the measurements of Soil Moisture and Ocean Salinity (SMOS) and Aquarius, two other satellite missions with L-band microwave radiometers operating in the protected band. Comparison with RFI of known location suggests that the algorithm is accurate to 1-2 km. The median distance between the locations reported by SMOS and this algorithm is 2.27 km. A study of the relationship between the localization error and the number of observations of RFI sources shows that the median localization error is about 2 km with 12 observations and about 1 km with 30 observations.

The Ultra-Wideband Microwave Radiometer observes scene brightness temperatures over the frequency range 0.5-2 GHz, which primarily includes frequency bands that are not protected for passive microwave observations. This document presents UWBRAD's RFI mitigation algorithms and examples of the RFI environment encountered during a September 2016 flight campaign that included flights in Canada and Greenland.

The Ultra-Wideband Microwave Radiometer is a novel pseudo-correlation radiometer design measuring scene brightness temperatures from 0.5-2 GHz created under NASA's Instrument Incubator Program. This document analyzes the design and operation of the radiometer, the accuracy and stability of the brightness temperatures it produces, and presents initial results from a field campaign conducted in Greenland in September 2016.

The CubeSat Radiometer Radio Frequency Interference Technology Validation (CubeRRT) mission is developing a 6U CubeSat system to demonstrate radio frequency interference (RFI) detection and filtering technologies for future microwave radiometer remote sensing missions. CubeRRT will perform observations of Earth brightness temperatures from 6-40 GHz using a 1 GHz bandwidth tuned channel and will demonstrate on-board real-time RFIS processing. The system is currently under development, with an expected launch date in mid-2018 followed by a one year period of on-orbit operations. Development of the CubeRRT spacecraft, radiometer instrument, and concepts of operation are described in this paper.

NASA's Soil Moisture Active and Passive (SMAP) satellite was launched in January 2015 to provide global measurements of soil moisture and freeze/thaw state. Soil moisture products are derived from SMAP radiometer measurements acquired at L Band (1.4 GHz). Even though this is a protected band, unauthorized transmitters emitting either within the band or in adjacent bands cause radio frequency interference (RFI). Because RFI contributions corrupt the radiometer measurements and therefore can lead to biases in retrieved soil moisture, the SMAP radiometer includes special hardware to enable RFI detection and filtering using multiple detection algorithms. This paper investigates the performance of SMAP's RFI detectors, which include pulse, cross-frequency, kurtosis, and polarimetric methods, as a function of the power of the RFI sources. Methods for examining residual RFI remaining after detection and filtering is applied are also discussed.

This presentation will include an overview of the recently launched NASA CYGNSS mission Level 1 calibration algorithms and their on-orbit validation [1], [2]. The validation of the Level 1 calibration will be performed in several steps, including a) a detailed noise floor analysis to assess the observed on-orbit noise power levels over the open ocean, b) multiple consistency checks using a forward model and co-located ocean wind and wave truth reference data and c) a term by term error analysis of all the non-ocean corrections applied to the final sigma0 estimates. An outline of the Level 1a (calibration from raw Level 0 instrument counts to units of watts for the received power) and the Level 1b (calibration from watts to bistatic scattering cross section) algorithms are each shown below. Three key components of the Level 1a calibration will be presented, namely, an analysis of the instrument (alone) and antenna noise characteristics over the ocean, a study of the range of received power levels from the surface, and comparisons with a forward model. The key components of the Level 1b calibration presented here will include validation of the main corrections applied to arrive at a surface sigma0 estimate, including receiver antenna gain, GPS transmitter and scattering area corrections.

A new space-borne mission based on a multi-channel microwave radiometer in the frequency range 0.5-2 GHz as been recently approved by the Italian Space Agency for a preliminary concept study. The innovative instrument will be devoted to the study of the Cryosphere and in particular on sea ice volume, ice sheet temperature and soil status. Scientific objectives and first mission concept are presented here and in depth discussed at the conference.

The systematic retrieval of near surface soil moisture (SSM) fields at high resolution (e.g., 0.1-1.0 km) is a challenging task that requires the exploitation of new retrieval algorithms and SAR data with advanced observational capabilities (in terms of spatial/temporal resolution, radiometric accuracy, very large swath, long-term continuity and rapid data dissemination). The launch of the Sentinel-1 (S-1) constellation provides these capabilities and calls for the development and validation of pre-operational SSM products at high resolution. The objective of this paper is to present and initially assess a SSM retrieval algorithm developed in view of S-1 data exploitation. The activity is supported by a large scientific community engaged in fostering a more effective interaction between researchers working in the field of high and low resolution SSM retrieval.

In this paper we discuss the design and development of the Radiometer Digital Backend (RDB) of the CubeSat Radiometer Radio Frequency Interference Technology (CubeRRT) validation mission. We present a brief introduction of the mission and the Radio Frequency Interference (RFI) detection and mitigation algorithm. The digital backend developed for the CubeSat is presented. The digital backend has unique capabilities of taking in wide bandwidths of up to 1GHz and can perform on-board complex operations to detect and filter out RFI in real-time. We present a few initial results of the backend spectrometer leading to full-system integration and test.

The CYGNSS (Cyclone GNSS) Mission is a constellation of 8 micro-satellites successfully launched in December 2016. Each satellite carries a GNSS-R (Global Navigation Satellite System Reflectometry) receiver which forms a Level-1 delay-Doppler map (DDM) measurement of reflected GPS L1 C/A-coded signals off the surface of the Earth. A very similar instrument is also operating onboard the TechDemoSat-1 (TDS-1) satellite. Prior to launch, the CYGNSS End-to-End Simulator (E2ES) was developed in order to simulate CYGNSS measurements and develop Level-2 ocean surface mean-square-slope (MSS) and wind speed retrieval algorithms. As part of initial validation process, this paper will present a detailed comparison between the downlinked Level-1 DDM data (from both TDS-1 and CYGNSS) and those predicted by high-fidelity CYGNSS forward model. This comparison includes a statistical analysis of DDM data pixels and their residuals with respect to simulated waveforms as a means of analyzing the on-orbit properties of the instrument, identifying outliers, as well as validating predicted scattering models, particularly the model's predicted dependence on incidence angle and wind speed.

A modeling study investigating the influence of wind direction on spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) near specular observations of the sea surface is reported. Because the delay doppler maps (DDMs) measured in GNSS-R include some non-specular contributions even for “specular” portions of the DDM, the study performs an examination of near specular DDM variations with wind direction using the widely used Geometrical Optics approximation of surface scattering for a surface described with the non-Gaussian Cox-Munk slope probability density function. Variations with wind direction of the normalized radar cross section (NRCS) mapped onto the surface are examined, and it is shown that these variations are negligible for surface portions contributing to the near specular portion of the DDM.

The Cyclone Global Navigation Satellite System (CYGNSS) mission launched Dec. 2016 and will provide ocean surface wind speed measurements from an eight satellite constellation using GPS reflectometry observations. The nature of CYGNSS coverage results in some locations on Earth experiencing multiple wind speed measurements within a short period of time (a “clump” of observations in time resulting in a “rapid revisit” series of measurements). Such observations could seemingly provide indications of regions experiencing rapid changes in wind speeds, and therefore be of scientific utility. Simulation studies of these measurements have been conducted including an analysis of the statistics of the duration of a “clump” and the maximum clump durations. The results show that the duration of a “clump” can extend as long as a few hours at higher latitudes, with gaps between clumps ranging from 6 to as high as 12 hours depending on latitude. The conference presentation will report initial results from “rapid revisit” analyses using on-orbit CYGNSS measurements.

Effect of roughness on forward physical model for Brightness Temperature of Antarctic ice sheets is presented. The Antarctic ice sheet which is characterized by layers of ice with permittivity fluctuations in addition to random rough interfaces. In order to investigate effect of roughness on brightness temperature, we only consider top 20 layers of ice sheets rough and all other layers with flat interfaces. The comparison between the results of the model and ESA's soil moisture ocean salinity (SMOS) brightness temperature show that the influence of roughness can significantly increase horizontally polarized thermal emission while leaving vertically polarized emissions relatively unaffected.

The second-order small perturbation method is applied to investigate brightness temperature corrections caused by the rough interfaces of a two-layer medium. The spectral weighting functions of the two rough interfaces are extracted from the solution, and their properties examined. It is found that the functions are identical for the two interfaces as the spectral variable approaches zero, indicating an identical weighting of the surface height variance on each interface and an additive effect on the brightness temperature at nadir. Sample results for some realistic scenarios show that surface roughness in a two-layer medium can increase or decrease the observed brightness temperature at shallower angles, and in the case of a wideband measurement, can shift the interference pattern in frequency.

This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active-Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture retrievals using radar observations have been challenging in the past due to complicating factors of surface roughness and vegetation scattering. Here, physically based forward models of radar scattering for individual vegetation types are inverted using a time-series approach to retrieve soil moisture while correcting for the effects of static roughness and dynamic vegetation. Compared with the past studies in homogeneous field scales, this paper performs a stringent test with the satellite data in the presence of terrain slope, subpixel heterogeneity, and vegetation growth. The retrieval process also addresses any deficiencies in the forward model by removing any time-averaged bias between model and observations and by adjusting the strength of vegetation contributions. The retrievals are assessed at 14 core validation sites representing a wide range of global soil and vegetation conditions over grass, pasture, shrub, woody savanna, corn, wheat, and soybean fields. The predictions of the forward models used agree with SMAP measurements to within 0.5 dB unbiased-root-mean-square error (ubRMSE) and −0.05 dB (bias) for both copolarizations. Soil moisture retrievals have an accuracy of 0.052 m3/m3ubRMSE, −0.015 m3/m3bias, and a correlation of 0.50, compared toin situmeasurements, thus meeting the accuracy target of 0.06 m3/m3ubRMSE. The successful retrieval demonstrates the feasibility of a physically based time series retrieval with L-band SAR data for characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetation.

Non-Rayleigh distributed radar clutter is widely reported in studies of radar scattering from sea and land surfaces. Existing models of scattered field amplitude distributions have been developed primarily through empirical fits to the statistics of radar backscatter measurements. In contrast, this paper investigates a physics-based approach to determine the amplitude distributions of fields scattered from rough surfaces using Monte Carlo simulations and analytical methods, for both backscattering and bistatic configurations. The rough surface is represented using a “two-scale” model. An individual surface facet contains “small-scale” roughness, for which scattered fields are evaluated using the second-order small slope approximation. Individual surface facets are tilted by the slopes of the “large-scale” roughness in a given observation. The results show that non-Rayleigh amplitude distributions are obtained when tilting is performed, and that the departure from the Rayleigh distribution becomes more significant as the variance of the tilting slope increases. Further analysis shows that this departure results from variations in the mean scattering amplitude from a facet (the texture) as tilting occurs. The distribution of the texture is studied and compared with existing models. Finally, the distribution of the scattered field amplitude is modeled through the compound Gaussian model, first using the distribution of the texture, and then in terms of the probability density function of tilting slopes (which avoids the requirement of the knowledge of the texture distribution). The results from the above two methods are in good agreement and both agree well with the Monte Carlo simulation.

Many previous studies have shown the sensitivity of radar backscatter to surface soil moisture content, particularly at L-band. Moreover, the estimation of soil moisture from radar for bare soil surfaces is well-documented, but estimation underneath a vegetation canopy remains unsolved. Vegetation significantly increases the complexity of modeling the electromagnetic scattering in the observed scene, and can even obstruct the contributions from the underlying soil surface. Existing approaches to estimating soil moisture under vegetation using radar typically rely on a forward model to describe the backscattered signal and often require that the vegetation characteristics of the observed scene be provided by an ancillary data source. However, such information may not be reliable or available during the radar overpass of the observed scene (e.g., due to cloud coverage if derived from an optical sensor). Thus, the approach described herein is an extension of a change-detection method for soil moisture estimation, which does not require ancillary vegetation information, nor does it make use of a complicated forward scattering model. Novel modifications to the original algorithm include extension to multiple polarizations and a new technique for bounding the radar-derived soil moisture product using radiometer-based soil moisture estimates. Soil moisture estimates are generated using data from the Soil Moisture Active/Passive (SMAP) satellite-borne radar and radiometer data, and are compared with up-scaled data from a selection ofin situnetworks used in SMAP validation activities. These results show that the new algorithm can consistently achieve rms errors less than 0.07 m3/m3over a variety land cover types.

The ultra-wideband software-defined microwave radiometer (UWBRAD) is designed to provide ice sheet internal temperature by measuring low frequency microwave emission. A Bayesian framework is designed to retrieve the ice sheet internal temperature from simulated UWBRAD brightness temperature (Tb). Experiment results showed feasibility to estimate ice sheet internal temperature and improvement of priors.

The CubeSat Radiometer Radio Frequency Interference Technology Validation (CubeRRT) mission is developing a 6U CubeSat system to demonstrate radio frequency interference (RFI) detection and mitigation technologies for future microwave radiometer remote sensing missions. CubeRRT will perform observations of Earth brightness temperatures from 6-40 GHz using a 1 GHz bandwidth tuned channel, and will demonstrate on-board real-time RFI processing. The system is currently under development, with launch readiness expected in 2018 followed by a one year period of on-orbit operations. Project plans and status are reported in this paper.

The Ultra-wideband Software Defined Radiometer (UWBRAD) for ice sheet internal temperature sensing is designed to provide observations of ice sheet brightness temperatures from 500-2000 MHz. This presentation reports on current status of the instrument development, experimental results obtained to date, and plans for a September 2016 airborne deployment over Greenland.

The Soil Moisture Active Passive (SMAP) mission, launched January 31, 2015, provides global observations of 1.4 GHz Earth thermal emissions from space through its L-band radiometer. Although SMAP's radiometer passband lies within the protected 1.4-1.427 GHz band, both unauthorized in-band transmitters as well as out-of-band emissions from transmitters operating at frequencies adjacent to this allocated spectrum have been documented as sources of radio frequency interference (RFI) to the L-band radiometers on SMOS and Aquarius. Low level RFI (0.1-10 Kelvin) is especially problematic as it can be mistaken for natural variability and if left unmitigated can corrupt radiometer measurements leading to flawed retrievals. SMAP has an aggressive approach to RFI mitigation using an advanced digital microwave radiometer to provide time and frequency measurements as well as a comprehensive ground processing algorithm.

Surface soil moisture was retrieved globally by systematically correcting for the effects of vegetation and soil surface roughness. The retrieval is enabled by employing physical-models of radar forward scattering for individual vegetation types to account for vegetation scattering and absorption, and by constraining the surface roughness effect using time-series observations. The L-band SMAP multi-polarized (HH/VV/HV) σ° data acquired globally every three days were used from mid-April to early July, 2015. Assessment was conducted over 13 rigorously-chosen core validation sites covering a wide range of biomass types, biomass amount, and soil conditions. The soil moisture retrieval reached an accuracy of 0.06 m3/m3RMSE, a bias of 0.003 m3/m3, and a correlation of 0.56. The successful retrieval demonstrates that the physically-based retrieval method is capable of characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetation on a global scale.

A study of the polarimetric properties of near specular scattered fields from rough surfaces is reported using a circular polarization basis. Such studies are relevant for Global Navigation Satellite System- Reflectometry (GNSS-R) remote sensing of the sea surface. Particular emphasis in the study is placed on the use of field correlations for the remote sensing of wind direction over the sea surface.

The use of GNSS-R (Global Navigation Satellite System Reflectometry) for Earth remote sensing is becoming an increasingly attractive approach thanks to its inexpensive and passive method. While GNSS-R ocean altimetry has been studied extensively, previous studies have focused on the use of the delay waveform (DW) only in the retrieval of sea surface height. This paper presents sea surface height retrievals using a “full Delay-Doppler Map (DDM)” method, and applies the approach to measurements of TechDemoSat-1 (TDS-1), a recent space-borne mission. The End-to-End Simulator (E2ES) of GNSS-R waveforms developed for the CYGNSS mission is adapted for use with TDS-1 and applied as the forward model used in the retrieval process. Comparisons between measured and modeled DDMs have been conducted as a first step to validate this process. Retrievals of sea surface height using both the DW and full-DDM methods will be reported in the presentation. Potential methods for improving estimation error for future GNSS-R missions will also be described in the presentation.

A partially coherent low frequency microwave emission model for polar ice sheet is developed to operate from 0.5GHz to 2.0GHz predicting brightness temperatures. The emission from polar ice sheet over the wide frequency band is shown to be correlated with its temperature profile and affected by its density fluctuations. The density fluctuations creating weakly reflective internal interfaces cause the decay of wave coherence so that the ice sheet can be divided into blocks. The coherent wave interaction are accounted for within the block by full wave simulations while inter-block wave interaction are taken incoherently by cascading boundary conditions in radiative transfer. The layer thickness / correlation length of the density fluctuation cause distinct frequency spectrum of the brightness temperature. The air/ snow interface and intermediate snow layer interfaces are rough causing angular coupling and polarization coupling in microwave emissions, and affect the angular patterns of the brightness temperature.. We apply the small perturbation method to study the roughness effects of multiple interfaces. Results of vertical and horizontal emissivities are illustrated as a function of observation angles.

Radio-frequency interference (RFI) observations for L-band microwave radiometry during the SMAP Validation Experiment 2012 (SMAPVEX12) airborne campaign are reported in this paper. The soil moisture measurement campaign was conducted in summer 2012 near Winnipeg, MB, Canada, with additional RFI flights over Denver, CO, USA. The Passive Active L-Band sensor (PALS) radiometer of the Jet Propulsion Laboratory was used with a full-bandwidth direct sampling digital backend to measure and store predetection data that is fully resolved in time and frequency. Overviews of SMAPVEX12 and the receiver and digital backend used to collect data are presented, along with the data processing techniques used for RFI detection. Properties of the observed RFI are examined and compared with the results of previous studies. Finally, implications of the results are explained considering current missions such as NASA's Soil Moisture Active Passive Mission.

A dual-copolarization algorithm to classify inland open water bodies free of flooded vegetation using an L-band radar is presented and evaluated, with a view to applying the method to the Soil Moisture Active Passive (SMAP) mission for hydrological science and soil moisture retrieval applications. Past radar-based water body detection algorithms have applied a threshold to a single-polarization measurement, with water body detection declared if the observed cross section is less than the specified threshold. However, such methods are subject to ambiguities associated with scene variability and terrain slopes, making a universal threshold value difficult to derive and complicating the global application of such methods. Because SMAP will provide measurements in both HH and VV polarizations, the copolarization ratio is also available for water body detection. A threshold of -3 dB applied to the HH/VV polarization ratio is found effective in detecting water bodies at 40° incidence angle based on analysis of theoretical model predictions and measurements from airborne synthetic aperture radar and the spaceborne Aquarius scatterometer. When the water surface is calm and its radar response is very small (i.e., at the radar thermal noise level), the HH/VV ratio method fails. However, a combination of an HH/VV threshold (at -3 dB) and an HH threshold (at -25 dB) is shown to allow water body classification even in this situation. This proposed “combined” algorithm is assessed in four different geophysical scenarios. The resulting water body detection error is shown to be less than 10% for these cases, which satisfies SMAP requirements to allow accurate soil moisture retrieval, and the corresponding false alarm rate is smaller than 2%. The robustness of the proposed approach to subpixel heterogeneity has been also investigated. The performance of the algorithm remains sensitive to the noise level of the radar observations: for SMAP, a radar noise-equivalent sigma 0 of -28.5 dB or less is required in order to facilitate acceptable performance.

The National Aeronautics and Space Administration's (NASA) Soil Moisture Active and Passive (SMAP) mission, which was launched on January 31, 2015, is providing global measurements of soil moisture and freeze/thaw state. The SMAP radiometer operates within the protected Earth Exploration Satellite Service passive frequency allocation of 1400-1427 MHz. However, unauthorized in-band transmitters and out-of-band emissions from transmitters operating at frequencies adjacent to this allocated spectrum are known to cause interference to microwave radiometry in this band. Because measurement corruption by these terrestrial transmissions, which is referred to as radio-frequency interference (RFI), threatens mission success, the SMAP radiometer includes special flight hardware to enable the detection and filtering of RFI. Results from the first year of SMAP data show the presence of RFI with frequent occurrence over Asia and Europe. During the calibration/validation stage of the mission, the RFI detection and mitigation algorithms were modified to provide enhanced performance. Analysis of the L1B_TB products indicates good algorithmic performance with respect to RFI detection and removal. However, some regions of the globe (e.g., Japan) continue to experience complete data loss. This paper summarizes updates to the SMAP RFI processing algorithms based on prelaunch tests and on-orbit measurements, as well as RFI information obtained in SMAP's first year on orbit.

This paper discusses methods for using measurements of the backscattered power and the Doppler shift of radar signals scattered from the ocean surface to compute maps of phase resolved ocean wave fields. Results are compared with buoy and lidar measurements of ocean surface waves off the coast of southern California.

This paper aims at identifying suitable geometrical configurations of a passive satellite radar flying in convoy with an active spaceborne SAR. The work has been performed in the frame of the SAOCOM-CS scientific investigations. It is a small satellite that ESA is conceiving to fly in convoy with the Argentinian SAOCOM 1B to acquire bistatic radar data at L-band. The applications foreseen in the paper are the retrieval of soil moisture and crop biomass. It is shown by a model based investigation that retrieval performances can be improved by combining monostatic and bistatic measurements in geometric configurations requiring very high along track and across track baselines.

This paper investigates the algorithms that are used to predict the full polarimetric bistatic normalized radar cross-section of rough surfaces. These include small perturbation method (SPM), the physical optics (PO) approach, the small slope approximation (SSA) and the integration equation method (IEM) and its derivatives improved IEM and advanced IEM. The methods are then compared to ground truth values obtained from multiple Monte Carlo runs a numerical Method of Moments (MOM) code using the same surface statistics. Effects of using band-limited exponential instead of a true exponential correlation function for surface statistics are also explored. Mean L1-norm error values integrated over the hemisphere are given between AIEM and MOM and SSA and MOM.

We present simplified expressions for the cross-polarized backscatter of a randomly rough surface predicted by the second-order small-slope approximation (SSA2). The simplification is based on appropriate polynomial approximations of the SSA2 kernel function. We obtain numerically efficient expressions for the cross-polarized backscattering amplitude of a deterministic surface in the form of a single space integral involving only the surface elevation and the second (mixed) derivative of the surface elevation. The ensemble average normalized radar cross section is then derived under a Gaussian random process assumption for the surface. The resulting expression has the form of a Kirchhoff integral involving the roughness correlation function and its second- and fourth-order cross-derivatives. Further simplification is achieved for off-nadir observations using a high-frequency approximation; the result is an analytical formula involving only the resonant curvature and the radar-filtered mean square slope in the out-of-plane direction. A numerical validation of the simplified expressions is provided by comparison with exact SSA2 predictions in representative test cases. The dependence of cross-polarized backscattering on the incidence angle as well as wind speed and direction is then investigated for the case of a directional sea surface model. At near nadir incidence, a clear maximum in azimuth of the cross-polarized backscatter is observed for radar look directions 45° from the wind direction.

We investigate the degree to which ultrahigh frequency radio emission can be used to estimate subsurface physical temperature in the polar ice sheets. We combine electromagnetic emission forward models with plausible models of depth-dependent physical properties in the ice sheet. Temperature models are parameterized with variables including accumulation rate, geothermal heat flux, and surface temperature. Scattering is parameterized using empirical observations of grain growth combined with measured densities. Electromagnetic absorption is modeled using dielectric dispersion processes and semiempirical models based on observations. Our models illustrate that information about East Antarctic ice sheet temperature from near the surface to near the base can be gleaned from ultrawideband radiometer data. Based on our modeling study, we illustrate an instrument concept to measure ice sheet temperature profiles comprising a novel ultrawideband radiometer.

Many quantities describing ice sheet dynamics can be measured via remote sensing. However, subsurface ice sheet temperature, a very important parameter which determines in part internal deformation and ice flow, is not currently measured remotely. Direct knowledge is available only through measurements from a small number of boreholes. This paper presents the concept of utilizing microwave radiometry in the 0.5–2GHz frequency band to probe subsurface ice sheet temperatures. Ice sheet geophysical properties and the resulting microwave emission are reviewed, and an initial retrieval algorithm for subsurface ice sheet temperatures is described. Finally an ultrawideband radiometer design to realize the proposed measurements is summarized.

Radio frequency interference observations during the SMAP Validation Experiment 2012 (SMAPVEX12) airborne campaign are reported in this study. The campaign was conducted in Summer 2012 near Winnipeg, Canada with additional flights over Denver, CO. The Passive Active L-Band Sensor (PALS) radiometer of Jet Propulsion Laboratory (JPL) was used with a full bandwidth direct sampling receiver (called IBOB) to measure and store data fully resolved in time and frequency. In this paper, an overview of the campaign, hardware details, signal processing, and RFI detection are explained. Finally, properties of the observed RFI and future work are discussed.

Since the SMOS satellite launch in 2009, its L-band radiometer data have been analyzed in depth by scientists worldwide and have resulted in significant steps forward in different disciplines. As primary objectives of the mission, the main research focus has been related to soil moisture and ocean salinity. However, the availability of a complete long-term, all-weather time-series of calibrated global brightness temperature data has enabled much broader research investigations on other topics such as the Cryosphere. SMOS data collected over central of Antarctica were also analyzed and whereas Tb is in general very stable in time it presents some intriguing spatial variations which are not yet fully explained. Using electromagnetic model simulations, and ancillary data for describing the physical parameters of the ice sheet, the observed variability and features in SMOS data are reproduced and explained.

A soil moisture retrieval algorithm is proposed that takes advantage of the simultaneous radar and radiometer measurements by the forthcoming NASA Soil Moisture Active Passive (SMAP) mission. The algorithm is designed to downscale SMAP L-band brightness temperature measurements at low resolution ( ~ 40 km) to 9-km brightness temperature by using SMAP's L-band synthetic aperture radar (SAR) backscatter measurements at high resolution (1-3 km) in order to estimate soil moisture at 9-km resolution. The SMAP L-band SAR and radiometer instruments are designed to provide coincident observations at constant incidence angle, but at different spatial resolutions, across a wide swath. The algorithm described here takes advantage of the correlation between temporal fluctuations of brightness temperature and backscatter observed when viewing targets simultaneously at the same angle. Surface characteristics that affect the brightness temperature and backscatter measurements influence the signals at different time scales. This feature is applied in an approach in which fine-scale spatial heterogeneity detected by SAR observations is applied on coarser-scale radiometer measurements to produce an intermediate-resolution disaggregated brightness temperature field. These brightness temperatures are then used with established radiometer-based algorithms to retrieve soil moisture at the intermediate resolution. The capability of the overall algorithm is demonstrated using data acquired by the airborne passive and active L-band system from field campaigns and also by simulated global dataset. Results indicate that the algorithm has the potential to retrieve soil moisture at 9-km resolution, with the accuracy required for SMAP, over regions having vegetation up to 5- kg/m2vegetation water content. The results show a reduction in root mean square error of volumetric soil moisture (40% improvement in the statistics) from the minimum performance defined as the soil moisture retrieved using radiometer measurements re-sampled to the intermediate scale.

A study of the bistatic scattering patterns of rough surfaces is reported. We utilize both approximate and numerically exact models for surface scattering, and focus in particular on the location of local minima in the normalized radar cross-section as a function of the polar and azimuthal scattering angles. It is shown that these minima locations are distinct for HH and VV polarized returns in the case of slight roughness, and that the minimum locations for VV polarization are dependent for this case on the permittivity of the surface. It is also shown that these behaviors are modified as the surface roughness increases. These results may be useful in the design of future bistatic methods for sensing rough surface properties; initial consideration of the remote sensing of surface permittivity for small height surfaces is provided as an example.

A comparison of model predictions with measurements of near-nadir normalized radar cross sections (NRCSs) of the sea surface at Ku- and Ka-bands is reported. Measurements of Airborne Precipitation Radar Second Generation (APR-2) from near nadir to 25°incidence angle, along with simultaneous wind truth from dropsonde observations, are compared with predictions of the “cutoff-invariant” two-scale model of sea scattering with the overall goal of assessing the model for possible future use in the APR-2 calibration process. The performance of the model as a function of wind speed and incidence angle is therefore emphasized. The measured data set, acquired primarily during the 2010 “Genesis and Rapid Intensification Processes” (GRIP) experiment, includes wind speeds from approximately 5 to 45 m/s. Model comparisons are limited by uncertainties in the wind fields due to limited dropsonde coverage; the data set is separated into “more reliable” (containing wind speeds of 5-20 m/s) and “less reliable” (wind speeds of 5-45 m/s) wind truth categories accordingly. Because a model of the sea spectrum is required for cutoff-invariant model predictions, comparisons with measured data are performed for three differing sea spectrum descriptions. It is found that a bias of less than ~ 1 dB over the wind speed range 5-40 m/s and a standard deviation less than 1 dB over the wind speed range 10-40 m/s can be achieved when using the “unified” sea spectrum description of Elfouhaily The model also provides error levels that are near uniform with respect to both incidence angle and wind speed.

A compact polarimetric (CP) radar system requires fewer measurements than a fully polarimetric (FP) system, thus allowing added flexibility in radar system design. Previous studies have shown the potential of using compact polarimetry for radar remote sensing of soil moisture. This paper extends previous studies by considering a time series data cube retrieval algorithm and measurements in the presence of vegetation. Vegetation information is assumed to be provided by an ancillary data source in the retrieval process. The performance of an algorithm for reconstructing FP information from CP measurements of vegetated soil surfaces is also examined. The results of the study show that only a modest degradation in soil moisture retrieval performance occurs when compact-pol measurements are used in place of full-pol data.

The Soil Moisture Active Passive (SMAP) radiometer operates in the L-band protected spectrum (1400-1427 MHz) that is known to be vulnerable to radio-frequency interference (RFI). Although transmissions are forbidden at these frequencies by international regulations, ground-based, airborne, and spaceborne radiometric observations show substantial evidence of out-of-band emissions from neighboring transmitters and possibly illegally operating emitters. The spectral environment that SMAP faces includes not only occasional large levels of RFI but also significant amounts of low-level RFI equivalent to a brightness temperature of 0.1-10 K at the radiometer output. This low-level interference would be enough to jeopardize the success of a mission without an aggressive mitigation solution, including special flight hardware and ground software with capabilities of RFI detection and removal. SMAP takes a multidomain approach to RFI mitigation by utilizing an innovative onboard digital detector back end with digital signal processing algorithms to characterize the time, frequency, polarization, and statistical properties of the received signals. Almost 1000 times more measurements than what is conventionally necessary are collected to enable the ground processing algorithm to detect and remove harmful interference. Multiple RFI detectors are run on the ground, and their outputs are combined for maximum likelihood of detection to remove the RFI within a footprint. The capabilities of the hardware and software systems are successfully demonstrated using test data collected with a SMAP radiometer engineering test unit.

The SMAP RFI detecting digital backend performance is characterized using real-environment L-band RFI data from the SMAPVEX 2012 campaign. Various types of RFI signals are extracted from the airborne campaign dataset and fed to the SMAP radiometer using an Arbitrary Waveform Generator (AWG). The backend detection performance is tested, and missed-detections are further investigated. Initial results indicate RFI detection performance for the SMAP digital backend is acceptable.

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission has been providing L-band brightness temperature observations of the Earth since its launch in November 2009. Radio frequency interference (RFI) is clearly present in SMOS data, and RFI detection and mitigation are a challenging problem. Furthermore, the interferometric nature of SMOS observations can cause RFI artifacts in SMOS measurements. This letter reports an analysis of the characteristics of SMOS RFI in North America, including a study of RFI artifacts and a method for their removal. Polarimetric properties and statistics of the resulting observations after artifact removal are also examined as an initial step in characterizing the “true” RFI sources observed in North America.

The possibility of recovering sea surface wind vectors from near-nadiral cross-track Ku- or Ka-band backscatter measurements using a measuring geometry similar to that of the Airborne Precipitation Radar 2 is discussed. The cross-track scanning geometry includes diversity in both elevation and azimuth angles, allowing the possibility of both wind speed and direction retrieval to within a 180°direction ambiguity. A simulation study of wind vector retrieval accuracy is performed based on the use of the “cutoff-invariant two-scale model” of sea surface backscatter returns. The results show that a maximum likelihood retrieval approach utilizing data from the cross-track scan can provide reasonable wind vector retrieval accuracy.

Measurements of both the Soil Moisture and Ocean Salinity (SMOS) and Aquarius L-band microwave radiometers show a significant presence of radio frequency interference (RFI), although they operate in a protected frequency band where transmission is prohibited. RFI detection and mitigation remain a challenging problem for both missions, especially for low or moderate (i.e., on the order of 10 K or less) amplitude contributions. An algorithm for low-level source detection and mitigation is already included in Aquarius data sets, and both Aquarius and SMOS have distinct attributes that can potentially enable further improvements in detection and mitigation of these sources to some degree. The combination of SMOS and Aquarius data sets may enable further future improvements as well. Initial efforts toward this goal are reported in this paper. Similarities and differences in RFI effects on SMOS and Aquarius are examined, with a particular focus on instrument properties that cause differences in received RFI power in SMOS and Aquarius observations of a specific source. A study is also performed of SMOS observations for regions reported by Aquarius to contain “low-level” RFI. It is shown that the detection of these sources in the SMOS data set is challenging and that the dependence of the SMOS third and fourth Stokes parameters on incidence angle makes the polarimetric features of SMOS difficult to utilize for low-level source detection. However, an angular fitting procedure suggested previously in the literature can, in some cases, detect such sources in horizontal and vertical polarizations.

A numerical study of sea surface range-resolved Doppler spectra using low-grazing-angle backscatter measurements is described. Backscattered fields as a function of frequency are computed using the method of moments (MOM) for a single realization of a 1-D oceanlike surface profile as the realization evolves in time. Transformation into the range-Doppler domain enables examination of properties of the resulting Doppler spectra (for both HH and VV polarizations) and their relationship to properties of the surface profile. In general, a strong correspondence between the “long-wave” orbital velocity of the surface projected along the radar line of sight and the Doppler centroid frequency is observed for visible portions of the surface, as well as some evidence of relationships between the “width” of the Doppler spectrum and variations of the projected velocity in time at a given range point. Evidence of similar relationships even in some shadowed portions of the surface is also provided. Doppler spectra from HH and VV polarizations are qualitatively similar, despite differences in total power levels, although the portion of shadowed surface points from which Doppler information is available is somewhat larger in VV polarization. A further examination is conducted using backscattered fields computed with a single-scattering method, which neglects shadowing and any multiple-scattering effects. The remarkable similarities observed between MOM and single-scattered Doppler spectra even in some shadowed portions of the surface suggest that non-line-of-sight propagation effects do not significantly influence Doppler properties in such regions.

The objective of this paper is to investigate the sensitivity of cross-polarized backscatter to soil moisture content (mv) using experimental and simulated data. The experimental data set consists of co- and cross- C- and L band radar and ground data collected over bare fields by the University of Michigan in 1992 and during the Italian ENVISAT 2003 campaign over Matera (Italy), and over wheat fields during the European Space Agency AgriSAR 2006 and 2009 campaigns over DEMMIN (Germany) and Flevoland (The Netherlands), respectively. The simulated data set has been generated by merging a first-order Radiative Transfer model with a second-order Small Slope Approximation model. Preliminary results show that the model can reproduce the observed sensitivity of cross-polarized backscatter to mv. However, the modelled cross-polarized backscatter is biased with respect to the observations, suggesting that a single scale soil roughness is not sufficient to reproduce the backscatter level observed over fairly smooth surfaces.

The NASA Soil Moisture Active and Passive (SMAP) mission will measure soil moisture with a combination of L-band radar and radiometer measurements. We present an assessment of the expected impact of radio frequency interference (RFI) on SMAP performance, incorporating projections based on recent data collected by the Aquarius and SMOS missions. We discuss the impacts of RFI on the radar and radiometer separately given the differences in (1) RFI environment between the shared radar band and the protected radiometer band, (2) mitigation techniques available for the different measurements, and (3) existing data sources available that can inform predictions for SMAP.

Predictions of the fourth-order small perturbation method (SPM) are examined for scattering from two rough surfaces in a layered geometry. Cross-polarized backscatter, in particular, is emphasized because use of the fourth-order SPM is required to obtain this quantity. The formulation of the SPM fields and incoherent ensemble-averaged normalized radar cross sections (NRCSs) up to the third and the fourth order in surface rms heights, respectively, are reviewed. It is shown that the fourth-order NRCS includes distinct contributions from upper and lower interface roughnesses, as well as an “interaction” term that couples the upper and lower interface roughnesses. A comparison with NRCS values computed using the “numerically exact” method of moments in the full bistatic scattering pattern is shown for verification, and NRCS values at the second and the fourth order are compared in order to assess the convergence of the SPM series. Although the number of parameters inherent in the two-layer rough surface scattering problem makes an exhaustive study of scattering effects difficult, several illustrative examples are presented to capture a range of scattering behaviors. The results emphasize the importance of interactions between the rough surfaces in producing cross-polarized backscattering and also indicate an increased significance of fourth-order contributions in the two-layer geometry as compared to the single-layer case.

A time-series algorithm is proposed to retrieve bare surface soil moisture and rms height using two copolarized (HH and VV) L-band backscattering coefficients (σ0). The retrieval approach inverts a forward model for radar scattering from an isotropic bare surface. Because real-time inversion of a complex forward model is often computationally impractical, the inversion is implemented using a precomputed lookup table representation of σ0obtained from numerical Maxwell model in 3-D simulations. The retrieval process assumes that surface roughness properties are constant during the time-series interval, so that only a single rms height estimate is produced for the entire time series. The use of this rms height estimate as a constraint simplifies the associated soil moisture retrievals at each time step. A Monte-Carlo simulation of this algorithm with 0.7 dB radar measurement error (1-sigma) shows that retrievals using six time steps outperform a “snapshot” method (which retrieves rms height and soil moisture at each time step) by a factor of about two in rms soil moisture error. A second study using measured data having 6 to 11 time steps shows an rms error of 0.044 cm3/cm3for soil moisture with a correlation coefficient of 0.89 between retrieved and in situ data. Surface rms height estimates are also found accurate to 10 to 30% of in situ measurements. It is also shown that retrieval performance is not sensitive to errors in knowledge of the surface roughness correlation length for most of the bare surface conditions examined.

A numerical study of the retrieval of sea surface height profiles from low grazing angle Doppler radar measurements is described. Backscattered fields computed using the method-of-moments for one-dimensional ocean-like surface profiles are used to examine properties of Doppler spectra versus range. "Discrete" behaviors observed in the Doppler spectra versus range are found to be related to similar behaviors in orbital velocity statistics obtained directly from the corresponding surface profiles. Differences between Doppler spectra are also observed between VV- and HH-polarizations, with VV-polarization showing smaller Doppler spectral widths in some situations. In order to improve understanding of the accuracies to be expected in surface profile retrievals from Doppler information, estimation errors for the Doppler centroid versus range are studied using a simplified signal model. Comparisons of the results of this signal model with the method-of-moments simulations show that shadowing and multi-path propagation effects cause errors in Doppler centroid estimation beyond those caused by speckle effects alone.

ESA's SMOS mission has been providing L-band brightness temperature observations of the Earth since launch in Nov. 2009. Radio frequency interference (RFI) is clearly present in SMOS data, and RFI detection and mitigation remains a challenging problem. The interferometric nature of SMOS observations also causes some RFI artifacts in SMOS measurements that do not reflect the actual brightness temperature values. This paper reports on an analysis of SMOS RFI in North America, including a study of RFI artifacts and a method for their removal. Properties of the remaining RFI sources are then examined after artifact removal.

A radar-based time-series algorithm is evaluated for retrieving soil moisture (from the surface down to 5 cm depth) and roughness using two co-polarized (HH and VV) backscatter cross-section measurements (σ0). The retrieval approach inverts a forward model for radar scattering from a bare surface using a pre-computed lookup-table representation of σ0obtained from Numerical Maxwell Model in 3D simulations. The retrieval process assumes that surface roughness properties are constant during the time series interval, so that only a single rms height estimate is produced for the entire time series. A study using measured data having 6 to 11 time-steps shows an rms error of 0.044 cm3/cm3for soil moisture with a correlation coefficient of 0.89 between retrieved and in-situ data. Surface rms height estimates are also found accurate to 10 to 30% of in-situ measurements. It is also shown that retrieval performance is not sensitive to errors in knowledge of the surface roughness correlation length for most of the bare surface conditions examined.

NASA's planned SMAP mission will utilize a radar operating in a band centered on 1.26 GHz and a co-observing radiometer operating at 1.41 GHz to measure surface soil moisture. Both the radar and radiometer sub-systems are susceptible to radio frequency interference (RFI). Any significant impact of such interference requires mitigation in order to avoid degradation in the SMAP science products. Studies of RFI detection and mitigation methods for both the radar and radiometer are continuing in order to assess the risk to mission products and to refine the performance achieved.

A numerical study of the retrieval of sea surface profiles from low-grazing-angle interferometric radar measurements is described. Backscattered fields computed using the method of moments for 1-D ocean-like surface profiles are used to examine statistical properties of the single-look interferometric phase estimator, in order to investigate the applicability of standard expectations for height retrieval accuracy in this problem. The results show that shadowing and multipath propagation effects cause errors in interferometric phase estimation beyond those caused by speckle effects alone. In addition, the decorrelation between the fields received at two antennas is found to be impacted by shadowing and multipath propagation effects, making standard models for this quantity inapplicable as well. These results show that modeling the expected performance of interferometric sea surface height retrieval approaches at low grazing angles is difficult at present, and that further research is required to address this issue.

Statistics of radio frequency interference (RFI) observed in the band 1398-1422 MHz during an airborne campaign in the United States are reported for use in analysis and forecasting of L-band RFI for microwave radiometry. The observations were conducted from September to October 2008, and included approximately 92 h of flight time, of which approximately 20 h of “transit” or dedicated RFI observing flights are used in compiling the statistics presented. The observations used include outbound and return flights from Colorado to Maryland, as well as RFI surveys over large cities. The Passive Active L-Band Sensor (PALS) radiometer of NASA Jet Propulsion Laboratory augmented by three dedicated RFI observing systems was used in these observations. The complete system as well as the associated RFI characterization approaches are described, along with the resulting RFI statistical information and examinations of specific RFI sources. The results show that RFI in the protected L-band spectrum is common over North America, although the resulting interference when extrapolated to satellite observations will appear as “low-level” corruption that will be difficult to detect for traditional radiometer systems.

In this study, we develop a combined active/passive technique to estimate surface soil moisture with the focus on the short vegetated surfaces. We first simulated a database for both active and passive signals under SMAP's sensor configurations using the radiative transfer model with a wide range of conditions for surface soil moisture, roughness and vegetation properties that we considered as the random orientated disks and cylinders. Using this database, we developed 1) the techniques to estimate surface backscattering and emission components and 2) the technique to estimate soil moisture with the estimated surface backscattering and emission components. We will demonstrate these techniques with the model simulated data and its validation with the airborne PALS image data from the soil moisture SGP'99 and SMEX'02 experiments.

The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey. SMAP will make global measurements of the soil moisture present at the Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy, and carbon transfers between the land and the atmosphere. The accuracy of numerical models of the atmosphere used in weather prediction and climate projections are critically dependent on the correct characterization of these transfers. Soil moisture measurements are also directly applicable to flood assessment and drought monitoring. SMAP observations can help monitor these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes. The SMAP mission concept will utilize L-band radar and radiometer instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP is scheduled for launch in the 2014-2015 time frame.

Previous studies of statistical MIMO radar detection performance have used a target model that consists of a large number of point scatterers located within a rectangular target area. These point scatterers have scattering amplitudes that are complex random variables and are spatially uncorrelated, so that the target is a white noise process in space. Spatial correlations are introduced into the target model in this paper, and the impact of these correlations on MIMO radar system detection performance is analyzed.

Spaceborne remote sensors operating at L-band and lower frequencies can significantly be affected by Faraday rotation (FR) as their signals pass through the Earth's ionosphere. A method of compensating for FR in multipolarization scatterometry is introduced, which utilizes an ancillary estimate of the FR angle to retrieve corrected polarized scattered powers. Simulation results are presented to demonstrate the behavior of the FR correction process when radar speckle, instrument errors, and errors in the ancillary FR angle estimate are introduced.

An analysis of the performance of a cross-frequency detection algorithm for pulsed sinusoidal radio frequency interference (RFI) is performed. The performance obtained is compared with that of pulse and kurtosis detection methods that have been previously reported. The results of the study show that the cross-frequency algorithm provides good performance in detecting pulsed sinusoidal RFI at high duty cycles, including the case of continuous sinusoidal interference. The use of the cross-frequency algorithm requires choice of a detection threshold that in practice can be estimated using measured data. The effect of this threshold estimation on the detector performance is also examined.

The electromagnetic (EM) bias is an important error term in sea-surface height estimation from satellite radar altimetry. While the EM bias has been studied extensively, previous studies have utilized hydrodynamic and EM models that require an a priori separation of the sea surface into “long” and “short” waves that are then treated separately. This paper presents a study of the EM bias that avoids this decomposition by employing a Monte Carlo procedure with numerical nonlinear hydrodynamic simulations coupled with numerical physical-optics methods for EM scattering from the sea surface. Due to the computational complexity of the approach, only long-crested surfaces (i.e., 2-D scattering problems) are considered. The formulation of the physical-optics model utilized is presented, along with a derivation of the standard Brown model for the long-crested surface case for comparison. The simulated pulse returns generally are in good agreement with the Brown model using the specular surface height probability density function. However, the influence of the EM frequency on the EM bias obtained is much smaller than that reported from satellite observations. Predicted biases are also examined as the range of length scales included in the surface profile is varied, in order to determine any apparent cutoff or length-scale separations that occur. It is found that the bias continues to increase as additional short waves are included in the surface spectrum, although a saturation occurs for surface length scales shorter than the EM wavelength.

The performance of a cross-frequency detector against pulsed sinusoidal Radio Frequency Interference (RFI) is analyzed theoretically. The effects of duty cycle and RFI strength are examined, and the detection performance of the cross-frequency algorithm is compared with that achieved by pulse and kurtosis detectors. The performance loss that occurs in the cross-frequency algorithm when an RFI source is not centered in a frequency channel is also quantified, and a computationally simple model for this loss is described.

Radio Frequency Interference (RFI) is a major concern for microwave radiometry. In September-October 2008, an airborne campaign for observing L-band RFI was conducted and included approximately fifty hours of flight time. The campaign included test flights in Grand Junction, Colorado, observations over soil moisture ground truth sites in Iowa and Maryland, transit and return flights from Colorado to Maryland, and dedicated RFI observing missions over urban areas. In this paper, the L-band digital backend and its RFI detection and mitigation algorithms are described. RFI statistics and examples from the airborne campaign are also presented.

The performance of the Shapiro–Wilk (S-W) test of normality for the detection of pulsed sinusoidal radio frequency interference (RFI) in microwave radiometry is analyzed. The study is motivated by the fact that the S-W test has been shown in the statistical literature to be effective in detecting a wide variety of non-Gaussian signal types. The basic properties of the S-W test statistic are reviewed, and the implementation of the test in digital hardware is discussed. Because the properties of the test statistic are difficult to obtain analytically, Monte Carlo simulations are utilized to compute performance. Results show that the test can provide reasonable performance in detecting pulsed sinusoidal RFI and that quantization of data has only a minimal impact on the sensitivity achieved. Detection performance is also compared with that of the kurtosis test for normality. It is shown that the S-W test produces comparable but degraded sensitivity compared to that of the kurtosis test in most cases while avoiding the “blind spot” associated with the kurtosis test for pulsed interferers having 50% duty cycle. Test performance is also shown to be improved ifa prioriknowledge of expected RFI pulse lengths is incorporated.

A numerical study of the retrieval of sea surface height profiles from low grazing angle radar observations is described. The study is based on a numerical method for electromagnetic scattering from 1-D rough sea profiles, combined with the ldquoimproved linear representationrdquo of Creamer for simulating weakly nonlinear sea surface hydrodynamics. Numerical computations are performed for frequencies from 2975 to 3025 MHz so that simulated radar pulse returns are achieved. The geometry utilized models a radar with an antenna height of 14 m, observing the sea surface at ranges from 520 to 1720 m. The low grazing angles of this configuration produce significant shadowing of the sea surface, and standard analytical theories of sea scattering are not directly applicable. Three approaches for retrieving sea height profile information are compared. The first method uses a statistical relationship between the surface height and the computed radar cross sections versus range (an incoherent measurement). A second method uses the phase difference between scattering measurements in two vertically separated antennas (ldquovertical interferometry) in the retrieval. The final technique retrieves height profiles from variations in the apparent Doppler frequency (coherent measurements) versus range and requires that time-stepped simulations be performed. The relative advantages and disadvantages of each of the three approaches are examined and discussed.

A proof-of-concept demonstration of through-wall sensing with microwave radiometry is described. A multifrequency microwave radiometer with 37 channels from 2.1 to 17.35 GHz was used in two experiments to observe objects through a cinder block wall of approximately 20-cm thickness. Measured data show the clear ability of the radiometer to detect thermal contrasts on the interior of the wall. A discussion of the basic physical processes involved in the measurement is provided. When compared with active systems, microwave radiometry for through-wall sensing faces significant challenges, including limitations in ranging, horizontal resolution, and corruption by radio-frequency interference, but also provides complementary capabilities, particularly with regard to thermal information. Further consideration of microwave radiometry appears warranted for applications where thermal information is of interest.

The performance of four algorithms for detecting the presence of pulsed sinusoidal interference in microwave radiometry is compared. The pulsed sinusoidal interference sources considered have unknown frequency, initial phase, amplitude, arrival time, and duration. The statistical properties of three of the algorithms are determined analytically, although numerical integrations are required in some cases in order to compute the obtained probabilities of detection. The performance of the fourth algorithm is evaluated using Monte Carlo procedures. Results show that three of the algorithms have a performance that is roughly comparable for the cases considered, while the fourth yields reduced sensitivity. A more detailed study of two of the algorithms, a simple energy detector called the pulse detection algorithm and a ldquopeakrdquo picking detector based on the use of data spectrograms, is also provided.

Two algorithms used in microwave radiometry for radio-frequency interference (RFI) detection and mitigation are the pulse detection algorithm and the kurtosis detection algorithm. The relative performance of the algorithms is compared both analytically and empirically. Their probabilities of false alarm under RFI-free conditions and of detection when RFI is present are examined. The downlink data rate required to implement each algorithm in a spaceborne application is also considered. The kurtosis algorithm is compared to a pulse detection algorithm operating under optimal RFI detection conditions. The performance of both algorithms is also analyzed as a function of varying characteristics of the RFI. The RFI detection probabilities of both algorithms under varying subsampling conditions are compared and validated using data obtained from a field campaign. Implementation details, resource usage, and postprocessing requirements are also addressed for both algorithms.

The effects of Faraday rotation on spaceborne polarimetric scatterometers are discussed. A method of exploiting an estimate of the Faraday rotation angle to retrieve co-cross polarization is outlined.

The Shapiro-Wilk (S-W) test is a test of normality recommended in the statistical literature for its effectiveness in detecting a wide-variety of non-gaussian signals. Tests for normality can be used for the detection of Radio Frequency Interference (RFI). However, so far only the kurtosis test has been used for this purpose. The performance of the S-W test against pulsed sinusoidal sources is studied in this paper as an alternative method of RFI detection. An overview of the S-W test is provided, and implementation of the test in digital hardware is discussed. Performance of the test was analyzed using Monte Carlo simulations due to the difficulties in obtaining an analytical solution. Results show that the test can provide reasonable performance in detecting pulsed sinu-soidal RFI, and the effect of quantization is minimal in the sensitivity obtained.

The performance of four algorithms for detecting the presence of short pulsed sinusoidal interference in microwave radiometry is compared. The pulsed sinusoidal interference sources considered have unknown frequency, initial phase, amplitude, arrival time, and duration. Statistical properties of three of the algorithms can be determined analytically, although numerical integrations are required in some cases in order to compute the obtained probabilities of detection. The performance of the fourth algorithm was evaluated using Monte Carlo procedures. Results show that three of the algorithms have a performance that is roughly comparable for the cases considered, while the fourth yields reduced sensitivity.

The electromagnetic bias is a critical error term in sea surface height estimation from satellite radar altimetry. While the electromagnetic bias has been studied extensively, most studies are based on low-order hydrodynamic and electromagnetic models. This paper proposes an alternate approach for electromagnetic bias studies by employing a Monte Carlo procedure with numerical non-linear hydrodynamic simulations coupled with numerical methods for electromagnetic scattering from the sea surface. A deterministic set of sea surface profiles and the corresponding altimeter pulse returns are produced in the simulation. The coupled electromagnetic/hydrodynamic methods can be chosen to tradeoff varying levels of physical fidelity with computational efficiency. The approach allows studies of the impact of various physical effects on the electromagnetic bias. Clear evidence of the electromagnetic bias can be observed in the simulated pulse returns in terms of a shift in the pulse return time.

A study of sea and ice sheet surface impulse responses measured at 150 MHz is reported. The presence of both coherent and noncoherent returns is observed due to the low frequency of observation, and attempts to interpret the observed wave-forms are presented. Further analysis using a Monte Carlo simulation of one dimensional surface impulse responses suggests that the physical optics theory should be applicable for modeling the observed waveforms so that they can be used in sensing ice sheet surface properties.

A numerical method for performing detailed investigations of modulation effects in sea backscattering is presented. The method is based on a combination of numerical hydrodynamic and electromagnetic codes as well as repeated simulations as the spectral content of the sea surface is varied. The results obtained can be useful in separating ldquotiltrdquo and hydrodynamic modulations in computed sea backscattering cross sections, and help to provide some insight into the need for ldquothree-scalerdquo modeling of sea surface returns. Sample results are presented to illustrate the basic process.

A description of the reduced local curvature approximation of third order for rough surface scattering is provided, including a history of the development of the method from the local curvature approximation. Sample results from the literature are also shown in order to illustrate the method's properties.

A study of cross frequency blanking for the mitigation of radio frequency interference in microwave radiometry is described. The data utilized were acquired in a 2005 flight over Texas cities, and include observations from 5.5 to 7.7 GHz at 0.1 MHz spectral resolution. A simple algorithm is described for detecting and mitigating interference, and the approach is shown to succeed in reducing the impact of both strong and low level interference.

The 17 papers in this special issue focus on subsurface sensing using ground-penetrating radar (GPR). These papers describe new approaches to subsurface sensing, including developments in electromagnetic wave propagation imaging/inversion of GPR data and antenna/radar technologies. Associated applications range from glaciology to pavement evaluation to landmine detection.

A band-limited exponential correlation function is presented for use in studies of rough-surface scattering. This model of surface statistics is developed by multiplying the power spectral density of a standard exponential correlation function surface with a Gaussian rolloff at high frequencies in order to limit the high-frequency spectral content of the surface. A parameter is introduced to describe the Gaussian rolloff, and the corresponding correlation function is determined. The primary proposed use of the model is in assessing the contributions of surface high-frequency content in the scattering process, particularly in approximate theories of surface scattering. Methods for incorporating this surface description into standard approximate scattering theories are described, and sample backscattering results provided to illustrate use of the model

A derivation of the fourth-order term in the small-slope approximation (SSA) of thermal emission from the sea surface is presented. It is shown that this term has the form of a fourfold integration over a product of two sea spectra for a Gaussian random process sea, thereby describing emission “interaction” effects among pairs of sea waves. An approximation for “long–long” wave interactions (i.e., the optical limit) is considered and shown to match the physical optics theory. Interaction effects between “long” and “short” waves are also considered, both through numerical and approximate evaluations of the fourth-order theory. The approximation developed has a form similar to an expanded “two-scale” model and enables comparisons of short-wave “tilting” effects between the two models in terms of spectrum independent “weighting” functions. The weighting functions obtained are found to be similar, but not identical, for the SSA and two-scale theories. In addition, azimuthal harmonics from the fourth-order SSA expansion of long–short wave interactions for a particular sea-surface model are compared against the full fourth-order theory and the two-scale model. Results again show the SSA and two-scale models to yield similar, but not identical, predictions.

A new model for rough surface scattering is presented; the model has a form similar to the small slope approximation (SSA) of Voronovich, but with modified kernel functions. As with the SSA, when including two field series terms in the solution the model matches the first- and second-order small perturbation method in the low-frequency limit. Unlike the SSA, the model also achieves agreement with the Kirchhoff approximation in the high-frequency limit even for penetrable surfaces. It is also shown that the new model achieves first-order tilt invariance for first-order SPM predictions. The new model is derived based on a previous extension of the local curvature approximation (LCA) to third order; the new model is termed the "reduced local curvature approximation of third order" (RLCA3) for this reason. Sample results for scattering from dielectric surfaces are presented to illustrate the new model and its relationship with other theories of rough surface scattering.

Radio-frequency interference (RFI) is a major limiting factor in passive microwave remote sensing and radio astronomy. A digitally based radiometer system has been developed to improve RFI mitigation through the use of high temporal and spectral resolution. The system includes a pulse-blanking algorithm that is capable of removing pulsed time-domain sources in real time. Cross-frequency mitigation is also possible in postprocessing through the use of the system's high spectral resolution. Several experiments have been conducted at L- and C-bands in recent years. Datasets from two particular campaigns are analyzed in this paper: ground-based observations at L-band in Canton, Michigan that emphasize pulse blanking and an airborne campaign at C-band over Texas and the Gulf of Mexico that emphasizes cross-frequency mitigation. Results and analyses are presented to quantify the RFI mitigation performance achieved.

The reduced local curvature approximation of third order (RLCA3) is a recently proposed model for rough surface scattering that matches the Kirchhoff approximation as well as the first-order and second-order small perturbation methods in appropriate limits. Predictions of bistatic scattering, thermal emission, and reflected atmospheric brightnesses from the RLCA3 model are presented in this paper through a Monte Carlo simulation process. The surfaces considered are realizations of an oceanlike spectrum and contain features ranging from 64 to 0.5 electromagnetic wavelengths. Results are compared with predictions from the commonly applied ldquotwo-scalerdquo theory of sea emission, as well as results from a previous similar study using the small slope approximation (SSA) of Voronovich. Results show a high level of agreement between RLCA3 and SSA predicted bistatic scattering patterns, but appreciable differences in predicted surface brightnesses, particularly in the third Stokes' parameter.

High-frequency approximations to the physical optics (PO) theory of scattering from exponentially correlated rough surfaces are examined and used to interpret the expected accuracy of the PO theory. As an introduction, a review of the PO theory for Gaussian-correlated surfaces is provided, and in this process an analytical summation of the PO series for specular scattering from Gaussian-correlated surfaces is obtained. A similar form is then derived for specular scattering from exponentially correlated surfaces and contrasted to the Gaussian case. These series allow the accuracy of the leading order term (i.e., the geometrical optics limit) in the high-frequency approximation of PO scattering for Gaussian or exponentially correlated surfaces to be investigated analytically. The leading order term in the high-frequency expansion for general PO scattering from exponentially correlated surfaces (Hagfors' Law) is then reviewed and interpreted in terms of a recently published theory of PO for surfaces with infinite rms slopes. The approximate ldquocutoffrdquo wavenumber from Hagfors' Law at which the high-frequency portion of the spectrum of an exponentially correlated surface can be truncated without producing large errors in PO predicted scattering is also discussed. Using this cutoff wavenumber, an approximate region of validity of the complete PO theory for exponentially correlated surfaces is obtained. The validity condition indicates that, for fixed surface statistics, the PO method produces accurate predictions of true surface scattering only up to a specific frequency, and that PO is inaccurate in the high-frequency limit. Comparisons of PO predictions with those of a Monte Carlo numerical simulation are used to show that the validity condition derived appears to provide a reasonable indication of PO accuracy. These results have important implications for current investigations of scattering from exponentially correlated surfaces and for the use of Hagfors' Law, as it is traditional to accept PO as the appropriate high-frequency limit in most existing approximate models of surface scattering.

In this paper, predictions from the small-slope approximation (SSA), the advanced integral equation model (AIEM), and the reduced third-order local curvature approximation (RLCA3) theories of rough surface scattering are compared with each other and with predictions obtained from numerical simulations for dielectric surfaces with Gaussian and exponential correlation functions. A discussion of the results obtained is provided, along with plans for continued investigations.

This paper describes C-band Radio Frequency In- terference (RFI) measurements made from NASA's WB-57 high- altitude aircraft using the PSR/CXI system of NOAA/ETL and the C-band Interference Suppressing Radiometer (CISR) digital backend of the Ohio State University (OSU) ElectroScience Laboratory. The observations discussed were performed during a test flight on Aug. 25th, 2005 over Texas cities as well as the Gulf of Mexico at a typical altitude of 62,000 feet.

The atmosphere has a significant effect on Wind- Sat measured brightnesses, particularly the linearly polarized channels. Due to the large size of these effects, measurement of the small azimuthal wind direction signal in the linearly polarized channels can be extremely difficult, and these channels are largely excluded or de-emphasized in current wind direction retrieval algorithms. In this work, attempts to determine the amplitudes of wind direction signals in WindSat linearly polarized channels are reported through a simple data binning procedure. Knowledge of these amplitudes as a function of environmental parameters will provide a first step in developing future wind direction retrieval algorithms that improve use of the linearly polarized channels. Several choices of the ground-truth data used in the binning process are examined, and the statistical significance of the harmonics obtained with each is quantified. Azimuthal harmonic coefficients using ground truth information from WindSat EDR 1.8.1 are found to be the most significant for moderate water vapor cases. The resulting dependence of the azimuthal harmonics on atmospheric parameters is investigated, and attempts to express this dependence in terms of atmospheric attenuation are described.

Passive microwave remote sensing at L-band is usually limited to the protected portion of the frequency spectrum (1400 to 1427 MHz). Operation outside this band is practically prohibited due to the presence of radio frequency interference (RFI), including pulsed-RFI from ground-based radars. To ad- dress this issue, a digital backend with real-time RFI mitigation has been developed. This instrument was utilized in ground- based observations of an air-route surveillance radar (ARSR) in Canton, MI in Summer 2005. This paper presents results from the campaign that demonstrate the capabilities of the system. I. INTRODUCTION

Retrieval of one dimensional ocean surface profile information is studied through the use of S and X band radar backscattering data at low grazing incidence. The required backscatter data is obtained through the use of numerical electromagnetic scattering codes. The simulations compute backscatter at multiple frequencies in each time step, so that range-resolved radar cross sections are obtained after an FFT operation. Profile retrievals are obtained through a simple "tilted Bragg" assumption, which allows local incidence angles on the surface to be directly determined from RCS data. These local incidence angles are then translated into surface slopes, and further integrated to construct the estimated profile. Initial results from this process are reported in this paper; further studies are in progress to quantify the overall accuracy achieved as a function of various surface and sensor parameters.

The spatial spectrum of short sea waves is locally modulated by the presence of longer waves or currents; in the remote sensing literature, this process is described by the "hydrodynamic modulation transfer function" (HMTF). Existing models for the HMTF utilized in remote sensing are based on approximations derived from consideration of conservation of wave action. However the accuracy of these approximations has been quantified only through comparison with experimental data; in such comparisons, numerous empirical models for terms such as wind forcing and breaking wave dissipation are required that make direct evaluation of the hydrodynamic effects difficult. A method for providing direct insight into the hydrodynamic modulation of short sea waves by longer waves is described in this paper, through use of numerical non-linear hydrodynamic codes for sea surface evolution. A Monte Carlo simulation process based on a stochastic spectrum of short waves propagating over a single deterministic long wave is described, including the data analysis techniques developed to extract a numerical HMTF from the simulated surfaces. HMTF values obtained from the simulations are compared to those from a first order wave action solution, and found to be in reasonable agreement.

Transmissions from ground-based systems in C- and X-bands present a significant challenge to the use of these bands for passive microwave remote sensing from aircraft and satellites. Because future missions plan to continue to use these frequencies, it is important to characterize and understand the nature of interference in as much of the candidate spectrum as possible. This paper presents a statistical analysis of interference observed in the continental U.S. using six months of data collected from the C- and X-band channels of the WindSat microwave radiometer. Our findings are consistent with those of previous studies by Li et al. and Njoku et al., which are based on data obtained from the Advanced Microwave Scanning Radiometer-EOS using somewhat similar center frequencies and bandwidths. Results show significant radio-frequency interference (RFI) at C-band, including brightnesses in horizontal and vertical polarizations in excess of 330 K, while X-band RFI is less obvious through direct examination of measured linearly polarized brightnesses. Evidence of lower levels of RFI is provided through use of the spectral and polarization indexes of Li et al., which reveal likely RFI contributions at X-band as well. Further confirmation of X-band RFI is obtained through analysis of the polarimetric channels, which are shown to provide direct evidence of RFI in contrast to the linearly polarized channels. A temporal analysis of the largest C-band RFI sources is also provided in an attempt to further understand their properties.

An efficient implementation of the two-scale model of sea surface thermal emission and atmospheric reflection is described. The model is applied in a study of the reflection of downwelling atmospheric radiation. Results show that reflected downwelling radiation can increase azimuthal variations of total observed brightnesses.

Corruption of C-band microwave brightness observations by radio-frequency interference (RFI) has been reported in recent data from orbiting radiometers; methods for mitigating these effects are of great importance for the design of future spaceborne microwave radiometers. One approach that has been suggested involves the use of multiple subchannels at C-band as opposed to a single channel; the use of multiple subchannels allows RFI to be detected and mitigated by analyzing relationships among subchannel brightnesses. While this approach has been utilized in previous airborne measurements, demonstrations of the RFI mitigation performance achieved have been difficult to obtain. To address this issue, an enhanced airborne system for observing radio-frequency interference effects on C-band microwave radiometers was developed, and is described in this paper. The system includes a traditional microwave radiometer with four C-band subchannels, so that RFI removal is possible using a subchannel mitigation algorithm. In addition, the system includes a digital receiver with the capability of providing high temporal and spectral resolution observations of interference. This high-resolution data allows improved understanding of RFI sources to be obtained, and also allows analysis of subchannel mitigation algorithm performance. Observations using the system in a test flight near Wallops Island, VA are described. Results show the four subchannel approach generally to be effective in mitigating the observed RFI sources, although examples are also illustrated using the digital receiver data to demonstrate failure of this approach. While studies of the digital receiver data alone could be performed to demonstrate further improvements in RFI mitigation, issues with this initial dataset limit the extent of such studies. Nevertheless, the results obtained still demonstrate qualitatively the improved RFI mitigation that can be achieved in brightness observations through the use of digital receivers

The spatial spectrum of short sea waves is locally modulated by the presence of longer waves or currents; in the remote sensing literature, this process is described by the hydrodynamic modulation transfer function (HMTF). Such modulations are important in understanding radar images of sea waves with water wavelengths longer than the radar range resolution. Existing models for the HMTF utilized in remote sensing are based on approximations derived from consideration of conservation of wave action. However, the accuracy of these approximations has been quantified only through comparison with experimental data; in such comparisons, numerous empirical models for terms such as wind forcing and breaking wave dissipation are required, which make direct evaluation of the hydrodynamic effects difficult. A method for providing direct insight into the hydrodynamic modulation of short sea waves by longer waves is described in this paper, through use of numerical nonlinear hydrodynamic codes for sea surface evolution. The codes applied are reviewed, and a Monte Carlo simulation process based on a stochastic spectrum of short waves propagating over a single deterministic long wave is described, including the data analysis techniques developed to extract a numerical HMTF from the simulated surfaces. HMTF values obtained from the simulations are compared with those from a first-order wave action solution and are found to be in reasonable agreement, although differences on the order of 10% are observed. A numerical evaluation of long wave effects on the short wave dispersion relation is also provided.

Abstract — Radio Frequency Interference (RFI) can adversely impact microwave passive remote sensing measurements, and prohibits passive observations outside protected portions of the radio frequency spectrum. A microwave radiometer including a digital backend with real-time RFI mitigation has been developed to address this issue. In this paper, we describe the radiometer design and its pulse blanking strategy. We also demonstrate the system using the sky as a target of observation. I.

Monte Carlo simulations are used to compute average direct surface thermal emission and reflected atmospheric radiation using the "active" small slope approximation of Voronovich. The surfaces considered are realizations of an ocean-like spectrum and contain features ranging from 64 to 0.5 electromagnetic wavelengths. The parallel computing approach of the study is described, and results are compared with predictions from the commonly applied "two-scale" theory of sea emission. Results show a reasonable level of agreement in a small height surface case, which degrades as the surface height is increased.

A derivation of the fourth order correction to the small slope theory of thermal emission from the sea surface is presented. It is shown that this correction has the form of a four-fold integration over a product of two sea spectra for a Gaussian random process sea. A sample result demonstrates that agreement with physical optics is achieved in the large scale surface limit.

Monte Carlo simulations are used to compute average direct surface thermal emission and reflected atmospheric radiation using the "active" small slope approximation of Voronovich. The surface used are realizations of an ocean-like spectrum, and contain features ranging from 64 to 0.5 electromagnetic wavelengths. The parallel computing approach used in these simulations is described, and results are compared with predictions from the commonly applied "two-scale" theory of sea emission. Results show a reasonable level of agreement in a small height surface case, which degrades as the surface height is increased

An airborne system for observing radio frequency interference at C-band is described. The digital receiver included has the capability of providing high temporal and spectral resolution of interference, as well as implementing simple mitigation strategies. Plans for observations with the system are discussed.

Microwave radiometers operating outside protected portions of the frequency spectrum can be adversely impacted by radio frequency interference. In this paper, we describe a new radiometer which coherently samples 100 MHz of spectrum and applies real-time RFI mitigation techniques using FPGAs. Experiments currently in progress to demonstrate the system are also detailed

The classical optical theorem for a scatterer in free space is useful in computing the total extinction cross section when the scattering amplitude in the forward scattering direction is known. In this letter, the classical optical theorem is extended to the case of a scatterer in the presence of a lossless half space. The extended optical theorem is derived based on energy conservation concepts, and the method of stationary phase is employed to obtain the final form. It is found that the total extinction cross section is related to the scattering amplitudes in the specular directions for reflected and transmitted fields. Numerical results are presented to illustrate use of the theorem for evaluating the energy conservation properties of an electromagnetic simulation.

A numerical model is applied in a Monte Carlo study of scattering from a three dimensional penetrable object below a lossy dielectric rough interface. Both time and frequency domain results are investigated to illustrate the relative importance of coherent and incoherent scattering effects in the sample problem considered. Results show that introducing a reduced transmission coefficient is reasonable for object coherent scattering predictions in this example, and that incoherent object/surface interaction effects approximately follow a simple scaling behavior as surface roughness is increased.

It is widely acknowledged that tree roots and other forms of buried biomass can have an adverse effect on the performance of ground-penetrating radars (GPRs). In this paper, we present analyses that examine that effect for ground-contacting GPR systems. A test site containing extensive root infiltration at Eglin Air Force Base, Florida, was excavated, and the root structure and soil were thoroughly characterized. A numerical simulator based on the discrete dipole approximation, which is an integral-equation-based method, was developed, validated, and subsequently used to compute scattering from root structures modeled by an ensemble of buried cylinders. An examination of the results is presented that quantifies the potential for false alarms and increased clutter due to buried roots.

Abstract — We describe measurements of radio frequency interference (RFI) in the 1200–1800 MHz band as observed from NASA’s P-3 research aircraft during a flight along the Mid-Atlantic coast of the U.S. at altitudes of 2,000 and 20,000 ft. Both power spectra and coherently-sampled waveform data were obtained. Our results indicate that the spectrum below 1400 MHz is typically dominated by pulses from ground based radars, which, while very strong, individually have transmit duty cycles of on the order of 0.1%. We detect but are unable to identify some relatively weak intermittent RFI inside the 20 MHz protected band centered at 1413 MHz. We detect no significant RFI above 1420 MHz, but the limited sensitivity of this particular experiment makes it impossible to rule out the presense of RFI at levels damaging to total power radiometry. Implications for radiometer design, including possible active countermeasures for RFI mitigation, are discussed. I.

Abstract — For increased sensitivity in L-band radiometry, bandwidths on the order of 100 MHz are desirable. This will likely require active countermeasures to mitigate RFI. In this paper, we describe a new radiometer which coherently samples 100 MHz of spectrum and applies real-time RFI mitigation techniques using FPGAs. A field test of an interim version of this design in a radio astronomy observation corrupted by radar pulses is described. I.

Three physical models for the microwave polarimetric brightness temperature of the sea surface are reviewed and compared. Two of these models are based on the composite surface theory, but use slightly different forms for the sea surface spectrum. The third model is based on a small slope approximation. All models are shown to predict similar zeroth, first, and second harmonic azimuthal variations of sea brightness and to show reasonable agreement with empirical results. However some discrepancies exist that is examined.

Previous studies have demonstrated that the West et al. (1987) numerical model for nonlinear hydrodynamic evolution of a sea surface produces significant features in calculated L-band backscattered Doppler spectra compared to a linear sea surface evolution model. These prior comparisons were limited, however, to a maximum wind speed of 2.0 m/s due to failure of the West et al. algorithm when steep short-wave features formed on the surface. In this paper, L-band Doppler spectra with the West et al. model are reported for wind speeds up to 5.0 m/s through the use of a curvature filter to reduce these steep short waves. The higher wind speed results again show significant deviations from those reported with a linear hydrodynamic model, including increased spectral broadening and polarization dependencies.

Plans for an experiment to test the relationship between near-nadiral multi-frequency brightness temperatures and rough surface spectra are described. The underlying small-slope theory of emission from a rough surface is reviewed, and modeling results are presented to suggest an experimental configuration to be used. The validity of predictions of the second order small slope theory is also investigated through comparison with higher order computations.

Computation of the higher-order small slope approximation (SSA) for electromagnetic scattering from a penetrable randomly rough surface is discussed, under the assumption of a Gaussian random process with an isotropic Gaussian correlation function. A simplified form for the first correction to the lowest order SSA theory is presented, and sample results illustrated to investigate the parameter space under which the first correction is appreciable. Reduction of the higher-order SSA to the physical optics approximation limit is also discussed for both perfectly-conducting and dielectric surfaces.

Previous studies have demonstrated that the West et al. (1987) model for non-linear hydrodynamic evolution of a sea surface realization produces significant features in calculated L-band backscattered Dopper spectra compared to a linear sea surface evolution model. Previous comparisons, however, were limited to a maximum wind speed of 2 m/s due to failure of the West et al. algorithm when steep short-wave features formed in the surface. In this paper, L-band Doppler spectra with the West et al. model are reported for wind speeds up to 4 m/s through the use of a suppression filter to reduce steep short-wave features. Results again show significant effects on Doppler spectra, including a strong polarization sensitivity at 80/spl deg/ observation angle.

Previous modeling studies have indicated that a multi-frequency radiometer could prove advantageous for shallow, sub-surface object sensing due to the oscillatory patterns in brightness temperature versus frequency that would be observed in the presence of a sub-surface object. Initial experimental results are reported in this paper from a multi-frequency radiometer system operating in the 2.1-6.5 GHz band. Measured brightnesses with sub-surface metallic and styrofoam targets are provided that demonstrate the predicted oscillatory behavior.

A comparison of the physical optics and small slope theories of emission from the sea surface is described. It is shown that the two theories produce identical results for "long wave" contributions to sea emission azimuthal variations up to third order in long wave surface slope when shadowing effects are neglected.

The small slope approximation (SSA) for polarimetric thermal emission from a rough surface is applied to study the up/down wind difference of sea surface brightness temperatures. A complete third-order theory is used, with results expressed in terms of an integral over the sea surface bispectrum. An approximation is developed to obtain emission contributions for surface length scales much larger than the electromagnetic wavelength and in this limit, the up/down wind brightness temperature difference is determined entirely by a combination of third moments of surface slope. Polarization dependencies in this limit however do not match those obtained from the Jet Propulsion Laboratory (JPL) WindRAD empirical model. Another approximation is derived to capture up/down wind emission asymmetry due to short waves which are modulated by longer waves. In this case, an integral of emission "weighting functions" over a pair of "reduced" bispectra is obtained, and examination of the weighting functions shows the importance of surface length scales comparable to the electromagnetic wavelength. The polarization dependencies of these weighting functions illustrate the possibility of matching the WindRAD model, but the absence of an effective hydrodynamic model for short gravity-capillary wave modulation by longer waves limits detailed comparisons.

Experimental results are reported for sensing of subsurface objects with a multifrequency radiometer (MFRAD) system. Properties of the MFRAD system are reviewed, and the calibration and experimental procedures are discussed. Results with subsurface metallic, styrofoam, and plastic targets are then provided that demonstrate an oscillatory behavior in brightness temperatures versus frequency in the presence of a subsurface object. Measured data are also compared with a simple layered medium brightness temperature model and show reasonable agreement with predicted trends of brightness temperatures versus frequency. The oscillatory behaviors versus frequency obtained in the presence of both metallic and nonmetallic subsurface objects should prove advantageous for designing object detection procedures.

Radar images of electromagnetic scattering from one-dimensional simulated ocean breaking waves are described. Backscatter results from 10-14 GHz at 60/spl deg/ to 80/spl deg/ incident angles are considered for surfaces that satisfy an impedance boundary condition. The generalized forward-backward method with spectral accelerations was used as an exact numerical solution to obtain backscatter returns from several surface profiles, and radar images are formed through back-projection tomography. Detailed investigations of the images are provided to clarify major and secondary scattering events, as well as the polarization dependence, and a ray-tracing analysis is performed to interpret multipath scattering mechanisms. By adding surface roughness outside the breaking region, small-scale roughness scattering effects are also investigated.

The small perturbation method (SPM) is applied to study thermal emission from a layered medium bounded by a slightly rough interface. Brightness temperatures are calculated to second order in surface height, including both specular reflection coefficient corrections and incoherent Bragg scatter terms. Unlike the homogeneous medium case, in which the SPM applied for emission predictions produces an expansion in surface slope, the theory remains a small height expansion, and convergence of the series is shown to depend on properties of the layered medium. Results from this theory can be applied in studies of soil moisture, sea ice, or sea surface remote sensing and buried object detection with microwave radiometers.

A numerical model for computing scattering from a three-dimensional (3D) dielectric object above or below a rough interface is described. The model is based on an iterative method of moments solution for equivalent electric and magnetic surface current densities on the rough interface and equivalent volumetric electric currents in the penetrable object. To improve computational efficiency, the canonical grid method and the discrete dipole approach (DDA) are used to compute surface to surface and object to object point couplings, respectively, in O(N log N), where N is the number of surface or object sampling points. Two distinct iterative approaches and a preconditioning method for the resulting matrix equation are discussed, and the solution is verified through comparison with a Sommerfeld integral-based solution in the flat surface limit. Results are illustrated for a sample landmine detection problem and show that a slight surface roughness can modify object backscattering returns.

Results from a Monte Carlo simulation of backscattering from one-dimensional (1-D) time-evolving sea surface models are reported. A numerical electromagnetic method based on an accelerated forward-backward approach is used to calculate backscattered returns from impedance surface profiles at incidence angles of 0/spl deg/ (normal), 40/spl deg/, and 80/spl deg/. Surfaces are initialized as realizations of a Pierson-Moskowitz spectrum and then stepped in time through a numerical hydrodynamic method. Results from three distinct hydrodynamic methods are compared: a linear evolution, the "improved linear representation" of Creamer et al. (1989), and the "Watson-West" approach of West et al. (1987). Instabilities in the West model due to formation of steep wave features limit the study to L-band backscattering for wind speeds less than 2 m/s, so that the surfaces considered are only slightly rough on an electromagnetic scale. The small slope approximation for electromagnetic scattering is shown to provide reasonable predictions in this limit. Statistics of the resulting surface profiles and backscattered fields are compared for the three models and are found to be similar in most respects. Backscattered field Doppler spectra, however, show differences, with the West model apparently capturing more nonlinear interactions in the surface evolution.

Second azimuthal harmonics of ocean surface brightness temperatures predicted by the second order small slope approximation (SSA) are compared to an empirical model based on WindRAD experiments performed by the Jet Propulsion Laboratory (JPL), Pasadena, CA. SSA predictions are illustrated for three differing models of the ocean surface directional spectrum, and results as a function of wind speed are shown to be in reasonable agreement with the WindRAD model at 19.35 and 37 GHz and at polar observation angles of 45/spl deg/, 55/spl deg/, and 65/spl deg/. None of the three spectral models, however, completely matches all the trends of the empirical data. A slight modification to one of the spectra is demonstrated to yield an improved agreement.

F-BM/NSA, H.T. Chou et al., Radio Sci., vol.33, p.1277-87, with computational complexity of O(N) is very efficient in method of moment (MoM) modeling of large-scale scattering problems from rough surfaces. The previous formulation for PEC surfaces is extended to treat impedance surfaces. Similarly, numerical experiment shows F-BM/NSA is far more efficient than the competitive BMIA/CAG in the order of magnitude.

Ka-band (27 GHz to 36 GHz) radar images of a 2.5-m red maple tree, measured in the Ohio State University ElectroScience Laboratory (ESL), Columbus, compact range, are presented. Radar images of the tree with and without leaves were obtained, as well as images of a 6 in diameter metal sphere obscured by the tree for investigation of attenuation effects. The large bandwidth (9 GHz) of these measurements provides a cm scale range resolution, so that backscatter from individual components of the tree canopy can be separated. In addition, measurements made as a function of azimuth angle in 0.1 degree steps allow inverse synthetic aperture radar (ISAR) images to be obtained with cm scale resolutions in down and cross range. A single scattering model, in which tree branches are represented as a deterministic collection of cylinders and leaves as a distributed collection of curved dielectric sheets, is combined with a detailed measurement of the tree geometry to provide theoretical ISAR images for comparison with the measured data. Although incomplete knowledge of tree geometry limits a direct quantitative comparison of the measured and modeled returns, a qualitative comparison of images shows that single scattering models may be sufficient for obtaining many features of foliage objects in Ka-band radar images.

A numerical model for scattering from sea ice based on the finite difference time domain (FDTD) technique is presented. The sea ice medium is modeled as consisting of randomly located spherical brine scatterers with a specified fractional volume, and the medium is modeled both with and without a randomly rough boundary to study the relative effects of volume and surface scattering. A Monte Carlo simulation is used to obtain numerical results for incoherent /spl upsi//spl upsi/ backscattered normalized radar cross sections (RCSs) in the frequency range from 3 to 9 GHz and for incidence angles from 10/spl deg/ to 50/spl deg/ from normal incidence. The computational intensity of the study necessitates an effective permittivity approach to modeling brine pocket effects and a nonuniform grid for small scale surface roughness. However, comparisons with analytical models show that these approximations should introduce errors no larger than approximately 3 dB. Incoherent /spl upsi//spl upsi/ cross sections backscattered from sea ice models with a smooth surface show only a small dependence on incidence angle, while results for sea ice models with slightly rough surfaces are found to be dominated by surface scattering at incidence angles less than 30/spl deg/ and by scattering from brine pockets at angles greater than 30/spl deg/. As the surface roughness increases, surface scattering tends to dominate at all incidence angles. Initial comparisons with measurements taken with artificially grown sea ice are made, and even the simplified sea ice model used in the FDTD simulation is found to provide reasonable agreement with measured data trends. The numerical model developed ran be useful in interpreting measurements when parameters such as surface roughness and scatterer distributions lie outside ranges where analytical models are valid.

The forward-backward method with a novel spectral acceleration algorithm (FB/NSA) has been shown to be an extremely efficient iterative method of moments (MoM) for the computation of scattering from one-dimensional (1D) perfect electric conducting (PEC) and impedance rough surfaces. The NSA algorithm is employed to rapidly compute interactions between widely separated points in the conventional FB method and is based on a spectral domain representation of source currents and the associated Green's function. For fixed surface roughness statistics, the computational cost and memory storage of the FB/NSA method are /spl Oscr/(N/sub tot/) as the surface size increases, where N/sub tot/ is the total number of unknowns to be solved. This makes studies of scattering from large surfaces, required in low grazing-angle scattering problems, tractable. In this paper, the FB/NSA method is extended to analyze scattering from two-dimensional (2D) rough surfaces. The NSA algorithm for this case involves a double spectral integral representation of source currents and the 3D free-space scalar Green's function. The coupling between two spectral variables makes the problem more challenging, and the efficiency improvements obtained for 2D surfaces are appreciable but not as dramatic as those for 1D surfaces. However, the computational efficiency of the FB/NSA method for 2D rough surfaces remains /spl Oscr/(N/sub tot/) as one of the surface dimensions increases. Comparisons of numerical results between the conventional FB method and the FB/NSA method for large-scale PEC rough surfaces show that the latter yields identical results to the former with a reduction of CPU time and only a slight increase in memory storage.

Temporal evolution of the ocean surface affects the received signal characteristics in a shipboard communication system. Predicting these time-varying properties is important in studying multipath fading problems. A statistical channel description to the second order is provided by knowledge of the coherent and incoherent power levels as well as the power spectrum of the received field. Several other time-dependent properties of a Gaussian channel can be determined from these statistics. In this paper, a method of moments (MoM) model for propagation over a one-dimensional (1D) time-evolving, perfectly conducting rough surface is applied to numerically study time statistics of propagation over the ocean. The ocean surface is described by a Pierson-Moskowitz spectrum and evolves in time according to a linear hydrodynamic dispersion relation. Due to the large size of propagation geometries in terms of the electromagnetic wavelength, an efficient numerical method is required to complete the simulation in a reasonable time. The recently developed forward-backward method with a novel spectral acceleration (F-B/NSA) technique is applied and enables time-evolving simulations for many realizations to be calculated so that reasonable statistics are obtained. Numerically obtained results for the coherent and the incoherent powers are illustrated. These results are compared with available analytical approximations to investigate the success of the approximate methods. Particular emphasis is placed on comparison with the Kirchhoff approximation, which provides reasonable predictions for smoother surface profiles and larger grazing angles.

A numerical model for polarimetric thermal emission from penetrable ocean surfaces rough in two directions is presented. The numerical model is based on Monte Carlo simulation with an iterative version of the method of moments (MOM) known as the sparse matrix flat surface iterative approach (SMFSIA), extended to the penetrable surface case through a numerical impedance boundary condition (NIBC) method. Since the small U/sub B/ brightnesses obtained from ocean surfaces (usually less than 1.5 K, or 0.5% of a 300-K physical temperature) require extremely accurate simulations to avoid large errors, a parallel version of the algorithm is developed to allow matrix elements to be integrated accurately and stored. The high accuracy required also limits simulations to near flat surface profiles, so that only high-frequency components of the ocean spectrum are modeled. Variations in nadir polarimetric brightness temperatures with spectrum low- and high-frequency cutoffs show the Bragg (or shortwave) portion of the spectrum to contribute significantly to emission azimuthal signatures, as predicted by the small perturbation or composite surface approximate theories. Quantitative comparisons with approximate methods show perturbation theory to slightly overestimate linear brightness temperatures, but accurately predict their azimuthal variations, while physical optics (PO) significantly underestimates both linear brightness temperatures and their azimuthal variations. Further simulations with the numerical model allow sensitivities to ocean spectrum models to be investigated and demonstrate the importance of an accurate azimuthal description for the ocean spectrum.

Analytical models for ocean surface polarimetric thermal emission based on the small perturbation method (SPM) have shown success in matching brightness temperature azimuthal variations from aircraft based measurements. It has also been shown that use of the small perturbation method for calculation of surface emissivity results in a series in surface slope, not surface height, so that the method remains accurate for large height surface emission even when it fails for the corresponding scattering calculations. This paper presents a detailed analysis of the SPM/small slope approximation (SPM/SSA) for ocean surface polarimetric thermal emission, and investigates the extent to which varying ocean surface length scales contribute to brightness temperature zeroth and second azimuthal harmonics. It is found that ocean waves of lengths both comparable to and much greater than the electromagnetic wavelength can contribute to these harmonics, depending on the extent to which the ocean surface spectral model places asymmetry in these length scales. In addition, the SPM/SSA is approximated for the contributions of both very long and very short ocean length scales compared to the electromagnetic wavelength, and it is found that both long and short wave contributions can be expressed in simple equations involving either standard or modified ocean surface slope variances.

A numerical study of 14-GHz backscattering from ocean-like surfaces, described by a Pierson-Moskowitz spectrum, is presented. Surfaces rough in one and two dimensions are investigated, with Monte Carlo simulations performed efficiently through the use of the canonical-grid expansion in an iterative method of moments. Backscattering cross sections are illustrated for perfectly conducting surfaces at angles from 0 to 60/spl deg/ from normal incidence, and the efficiency of the numerical model enables the composite surface theory to be studied in the microwave frequency range for realistic one-dimensional (1D) surface profiles at low wind speeds (3 m/s). Variations with surface spectrum low-frequency cutoff (ranging over spatial lengths from 21.9 to 4.29 cm) are investigated to obtain an assessment of composite surface model accuracy. The 1D surface results show an increase in hh backscatter returns as surface low-frequency content is increased for incidence angles larger than 30/spl deg/, while /spl nu//spl nu/ returns remain relatively constant, all as predicted by the composite surface model. Similar results are obtained for surfaces rough in two dimensions, although the increased computational complexity allows maximum surface sizes of only 1.37 m to be considered. In addition, cross-polarized cross sections are studied in the two-dimensional (2D) surface case and again found to increase as surface low-frequency content is increased. For both 1D and 2D surfaces, backscattering cross sections within 20/spl deg/ of normal incidence are found to be well matched by both Monte Carlo and analytical physical optics (PO) methods for all low-frequency cutoffs considered, and a comparison of analytical PO and geometrical optics (GO) results indicates an appropriate choice of the cutoff wavenumber in the composite surface model to insure an accurate slope variance for use in GO predictions. This choice of cutoff wavenumber is then applied in the composite surface theory for more realistic ocean spectra and compared with available experimental data.

Linear statistical temperature profile retrievals from nadiral passive 118-GHz O/sub 2/ spectra are demonstrated using time- and space-coincident microwave observations and radiosonde profiles. Separate retrievals are demonstrated for winter and summer midlatitude conditions in clear air over land; observations during both day and night are included. The retrieval operator is a linear-statistical minimum mean-squared-error estimator. A purely statistical retrieval operator circumvents the effects of radiative transfer model uncertainties and biases in either the radiosonde or Millimeter-wave Temperature Sounder data. The retrieved profile rms errors are approximately 0.7-1.2 K for either the winter or summer tropospheres.>

An experiment in which the third Stokes parameter thermal emission from a periodic water surface was measured is documented. This parameter is shown to be related to the direction of periodicity of the periodic surface and to approach brightnesses of up to 30 K at X-band for the surface used in the experiment. The surface actually analyzed was a "two-layer" periodic surface; the theory of thermal emission from such a surface is derived and the theoretical results are found to be in good agreement with the experimental measurements. These results further the idea of using the third Stokes parameter emission as an indicator of wind direction over the ocean.>