This paper presents the calibration process for an airborne polarimetric Global Navigation Satellite System Reflectometry (GNSS-R) sensor developed for the Rongowai project. We calibrate the sensor's dual-polarized antenna pattern and power measurement by comparing field data obtained from an inland lake surface with model predictions. The model evaluates the dual-polarized power of coherent polarimetric GPS signals reflected from inland water body surfaces with slight roughness caused by winds. The calibration results suggest a rotation of the polarimetric antenna gain pattern. A different scale factor is applied to the system’s dual-polarized power measurement for 1 and 2 millisecond coherent integration times. The absolute power calibration allows accurate surface reflectivity and normalized bistatic radar cross section (NBRCS) retrieval and enables future science applications.

Flooding is one of the deadliest and costliest natural disasters. Climate change-induced flooding events are increasing worldwide, disproportionately impacting low-income and developing communities. While early warning systems save lives, satellite-based observation systems are vital for the disaster relief and recovery phases. Current satellite-based operational flood products are largely based on either optical remote-sensing methods, which exhibit a limited ability to detect water through clouds and vegetation, or microwave remote sensing, which provides relatively low spatial and temporal resolution. New small satellite constellations using radar or GNSS reflectometry (GNSS-R) have been shown to enhance our ability to overcome these deficiencies. In this work, we quantify the performance of using GNSS-R measurements from the NASA Cyclone Global Navigation Satellite Systems (CYGNSS) satellite constellation to map surface water in South Sudan and the Sudd wetland in comparison with a set of representative operational products. We make quantitative comparisons of our results with operational flood products based on Visible Infrared Imaging Radiometer Suite (VIIRS) and MODIS and with C-band Sentinel-1 synthetic aperture radar. We find that our method detects 35.4% more surface water than Sentinel-1, while the VIIRS- and MODIS-based products underestimate by 4.8% and 83.7%, respectively. We use several metrics commonly used to evaluate classification performance: precision, true positive rate (TPR), true negative rate (TNR), F2-score, and the Matthews correlation coefficient (MCC) and assess the comparisons in this statistical framework. We discuss the consequences of our findings, including ways CYGNSS data may enhance current flood products and assist decision-makers and emergency managers.

When GNSS signals reflect off of the surfaces of lakes, rivers, wetlands, and other inland water bodies, the surfaces are often sufficiently smooth to produce coherent reflections. The observable produced from coherent reflections made by GNSS Reflectometry (GNSS-R) instruments exhibits particular features with respect to diffusely scattered signals by rough land and wind-driven oceans allowing detection of such smooth bodies. Several different GNSS-R coherence detection approaches have been reported in the literature and developed among the GNSS-R community over the last several years; however, the merits of each approach are difficult to compare because they are often applied to different scenarios and quantified in different ways, independently of each other. This paper provides a unified comparison of a wide variety of different GNSS-R coherence detection approaches, which is the most extensive published to date. The approaches are applied to a common data set from the NASA CYGNSS satellites that includes both the standard Level-1 DDM science product as well as raw baseband signal recordings. Additionally, simulated observables are generated with varying coherent and non-coherent reflection components to exercise algorithms over a wide range of SNRs and relative powers. Objective measures of accuracy are used to quantify the performance of each approach in the context of relative implementation complexity. Conclusions are presented on the pros/cons of the various methods as they relate to various applications such as real-time in-orbit coherence detection or post-processing on the ground.

This paper proposes a novel global-to-local (G2L) searching algorithm to find the locations of specular reflections over terrestrial surfaces for GNSS-R applications. In the proposed method, an initial coordinate of the specular reflection is first computed on a smooth WGS84 datum using the Fibonacci method. Second, a local coordinate frame that is centered at the initial WGS84 specular point (SP) is defined with respect to the local topography, and the G2L searching algorithm is applied to more precisely locate the specular reflection point. The effects of the complex land topography, including the local slope and incidence angles, are considered. This method is simulated for an airborne GNSS-R scenario where the receiver position is based on historical flight data from Gisborne to Wellington in New Zealand, where the results show that the finalized SP positions have been significantly shifted due to the complex topographical surfaces. This G2L method can be implemented to accurately track the location of reflected GNSS signal power from measured delay-Doppler maps (DDM) for land applications.

GNSS-R measurements from inland waters and wetlands show strong coherent reflections. These measurements can be utilized to detect the presence of surface water and to measure its extent; however, there are numerous geophysical phenomena may affect the received signal properties, such as wind induced waves and vegetation attenuation of both the electromagnetic signal and the surface water waves. Under-standing the impact of each of these geophysical effects in the inland water scene is useful for developing and assessing the capabilities of GNSS- R retrieval algorithms for detection and monitoring of dynamically changing inland water scenes. This paper proposes a combination of models to characterize these effects on the coherent GNSS reflection to a first order.

Earth observations are pivotal for developing informed, evidence-based sustainable practices and are of direct consequence to four of the seventeen UN Sustainable Development Goals (12–15). Among these, Earth observations using signals of opportunity such as GNSS-R have significantly evolved in recent years including expanding efforts to consider geophysical retrievals over complex and heterogeneous surfaces, primarily from space-borne missions. Airborne GNSS-R however has the advantages of higher resolution and signal strength and as such can provide critical data to inform algorithm development for complex environments. This paper presents the upcoming airborne Rongowai mission whereby Air New Zealand will fly a NASA-developed next-generation GNSS-R receiver as a unique international collaboration. Rongowai promises to deliver rich environmental records for sustainable land-use and water management including coastal and open ocean over many years at unprecedented spatial and temporal resolutions. We present representative coverage, and methodology for product development with specific focus on soil-moisture as it relates to land-use and water management gather

As climate change-induced global flooding increases in both frequency and magnitude, having accurate and timely flood maps becomes essential for humanitarian and future flood mitigation efforts. The Dartmouth Flood Observatory (DFO) aids humanitarian organizations and inundation observation research efforts through its archive of historical flood events extending back through 1985, as well as by providing current daily flood maps derived from a combination of observations, and also precipitation-based modeling products. Both could benefit from the addition of microwave observations that penetrate through clouds, rain, and vegetation, such as GNSS-R data now becoming available on a daily basis. In this work, we discuss a current collaboration to combine CYGNSS data with operational MODIS flood maps and evaluate the expected benefits for an example scenario over the recent anomalous flooding in South Sudan.

While CYGNSS exhibits a high revisit rate, the sparse, quasi-random tracks make it challenging to utilize data at short timescales for inundation mapping. In order to make use of the high revisit rate of CYGNSS, we implement a model-driven approach in which we compare simulated CYGNSS measurements over a binary water mask with actual CYGNSS measurements. We consider a simple water body like a reser-voir that has limited or no vegetation and exhibits dynamic changes in surface water extent within the CYGNSS mission timeframe. We find that our method has the potential to reliably detect changes in surface water extent down to 4 sq. km., corresponding to a 3% increase. Using simple, non-physics-based flood model outputs as inputs to the End-to-End Simulator (E2ES) can lead to the ability to estimate surface water extent over a given area using sparse CYGNSS measurements on sub-weekly timescales.

Global Navigation Satellite System (GNSS) Reflectometry uses reflected GNSS signals for Earth remote sensing applications. Absolute calibration of a Delay Doppler Map (DDM) requires an accurate estimate of the effective isotropic radiated power (EIRP) of the GNSS transmitter, e.g., Global Positioning System (GPS). However, variable transmit power by numerous Block II Follow-on (IIF) and II Replenishment-Modernized (IIR-M) GPS space vehicles has been observed due to their flex power mode. Nonuniformity in the GPS antenna gain patterns further complicates EIRP estimation. A dynamic calibration approach is developed to address GPS EIRP variability. It uses measurements by the direct received GPS signal to estimate GPS EIRP in the specular reflected direction and then incorporates it into the calibration of normalized bistatic radar cross section (NBRCS). Error analyses using Monte Carlo simulations and a root sum of squares (RSS) approach show that the resulting error in NBRCS is about 0.32 dB. Dynamic EIRP calibration instantaneously detects and corrects for power fluctuations in the GPS transmitters and significantly reduces errors due to GPS antenna gain azimuthal asymmetry. It allows observations with the most variable Block IIF transmitters (approximately 37% of the GPS constellation) to be included in the standard data products and further improves the calibration quality of NBRCS and geophysical data products.

Quantitative observations of dynamic changes in water extent and depth of the world's wetlands are currently limited by traditional remote sensing methods, which have difficulty observing surface water beneath dense vegetation and clouds. A novel remote sensing technique known as GNSS Reflectometry (GNSS-R) has shown great potential in the detection of terrestrial surface water beneath vegetation. The Cyclone Global Navigation Satellite System (CYGNSS) is a GNSS-R small satellite constellation that exhibits sub-daily revisit rates over tropical wetlands. In this work, we present a retrieval algorithm to predict water depth and surface water extent using CYGNSS observations over the Everglades. We test our algorithm over three regional approaches and varying smoothing filters. Results indicate that CYGNSS signal-to-noise ratio (SNR) is highly correlated with both water depth and extent over shallow, vegetated water.

NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission has been a pathfinder in the field of GNSS reflectometry (GNSS-R), with a constellation of 8 microsatellites measuring windspeeds over the entire tropics every few hours. More recently, terrestrial GNSS-R is being exploited to reveal records of soil moisture and surface water inundation dynamics. In an exciting partnership between NASA and New Zealand, Air New Zealand will accommodate and host a recently developed next-generation GNSS-R receiver (NGRx) and commercial aviation GPS omnidirectional antennas on a domestic Q300 aircraft. The result will be unprecedented high-resolution, wide coverage long-term records of soil moisture and inundation dynamics over New Zealand's diverse landscape and ecosystems, independent of cloud cover. Such data will support terrestrial calibration and validation of CYGNSS while simultaneously advancing the technology readiness level of the NgRx and enabling new remote sensing science investigations in New Zealand.

Recent results from CYGNSS have highlighted the importance of coherent GNSS reflections for measuring and mapping surface water. However, the GNSS-R instrument aboard CYGNSS was intended for measuring diffuse scattering from the ocean, and the way in which it processes measurements is not optimal for coherent reflections. The goal of this work is to review recent investigations into how on-board algorithms in future instruments can take full advantage of coherent GNSS-R measurements, especially with how they apply to observation of inland water. It is understood that the proper utilization of coherent reflections will open the door to a number of new and interesting science applications for GNSS-R. Several algorithms are proposed.

The v3 CYGNSS Level 1 calibration algorithm uses the direct signal received by the navigation channel to estimate the GPS EIRP for calibration of the NBRCS. Three sets of antenna patterns play an important role in this calibration algorithm, including the GPS transmit antenna and the CYGNSS zenith and nadir receive antennas. In this paper, we examine how the three antenna patterns are characterized on-orbit and how they are used by the CYGNSS Level 1b calibration algorithm. The impact of antenna pattern knowledge on calibration uncertainty is evaluated and discussed.

GNSS Reflectometry (GNSS-R) measurements are very sensitive to the presence of inland waters such as wetlands, floods, rivers and lakes. This paper reviews the basic characteristics of a GNSS-R ‘water detection’ research product, including resolution and temporal sampling of wetlands, and discusses the main known sources of errors. Additionally, a summary of GNSS-R applicability to the study of lakes is provided.

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.

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.

The accuracy of spaceborne ocean surface altimetry depends on precise knowledge of the altimeter satellite orbit. Previous studies of the potential utility of CYGNSS GNSS Reflectometry (GNSS-R) measurements for ocean altimetry have identified its orbit error as a limiting factor. To address this, a recent firmware upgrade to the CYGNSS satellites has enabled the downlink of additional GPS raw measurements from the navigation receiver and increased numerical precision of open-loop GNSS-R tracking information. In this paper, we present improvements to the accuracy of both the orbit determination and the ocean surface height retrievals as a result of these recent upgrades. JPL's GipsyX software is used to process 170 days of GPS navigation measurements for one of the 8 CYGNSS satellites. Incorporating high fidelity dynamic models and antenna group delay corrections, daily orbit overlaps throughout the period show mean RMS differences of 2.5 cm in height, 5.9 cm in cross-track, and 10 cm in along-track. Applying these new orbits reduced the standard deviation of retrieved sea surface height anomalies from 2.2 m to 1.9 m using 4 second smoothed measurements. Further improvements are expected using new ionospheric corrections and re-tracking methods currently in development.

The Cyclone Global Navigation Satellite System (CYGNSS) has recently shown exciting potential for GNSS reflectometry (GNSS-R) to resolve small-scale and dynamic hydrological features over land (such as rivers, lakes, wetlands, and urban flooding), even when obstructed by dense vegetation. Since CYGNSS is a small satellite constellation, sub-daily measurement frequencies provide a unique opportunity to observe short timescale changes. However, since CYGNSS observations occur in sparse, quasi-random tracks, it is more difficult to understand the true observability of events as compared to imaging instruments. Changes in SNR that would indicate a dynamic change in the scene are confounded by inherent variability due to other sources, including vegetation, geometry changes, instrument gain calibration, and surface roughness due to wind. While the literature does detail the use of CYGNSS measurements to map surface water changes, the lack of valid ground data makes it difficult to quantify the true accuracy. Here, we present results from a simulation study currently underway that utilizes a GNSS-R coherent scattering model to understand the observability and accuracy of CYGNSS measurements of dynamic changes in inland water bodies. The goal is to quantify the sensitivity and resolution of observations of dynamic spatial and temporal variations of inland water bodies.

Airborne GNSS-R instrument systems are typically only utilized for a limited number of aircraft flights to perform experiments, to test new instruments, and to collect data over specific targets (e.g. hurricanes). A new system is currently under development entailing the permanent installation of GNSS-R instruments on a commercial fleet of Air New Zealand Q300 regional aircraft. This novel and ambitious concept offers a fascinating and powerful system for the collection of science information over a large spatial region and short temporal scales. Here we present an exploratory analysis meant to quantify the merit of such a system as applied to these regional aircraft. We use simulations of realistic flight paths combined with GNSS orbit information to simulate GNSS-R measurement coverage. Results in this scenario confirm the exciting potential of a next-generation GNSS-R receiver.

Current GNSS-R instruments, such as those used aboard the CYGNSS and TDS-1 satellites, form delay-Doppler maps (DDMs) using fixed integration schemes. The reflected GNSS signal is coherently integrated with a local replica signal and then non-coherently integrated to form a DDM measurement. For scenes dominated by diffuse scattering (i.e. most land and ocean surfaces at typical incidence angles), this approach works well given the short reflected signal coherence time that does not vary significantly over the typical range of incidence angles. However, the coherence properties of the reflected signal change significantly in some circumstances, such as over inland water bodies, coastal areas, wetlands, and at grazing incidence angles over the ocean and land. In this study, we investigate the possible benefits of a receiver adapting its coherent integration time to the instantaneous properties of the reflected signal. The algorithm proposed uses the complex DDM samples to estimate the coherence time efficiently on-the-fly. These estimations are then used to adapt the coherent integration time in the receiver to form DDM measurements. Example results using raw signal data collected from CYGNSS will be presented.

Spaceborne GNSS Reflectometry (GNSS-R) measurements over inland waters have exhibited strong coherent scattering. The strong reflected signal from a relatively small spatial extent (several km) is highly sensitive to surface waves. This sensitivity can be leveraged to estimate wave height profiles across inland waters. Coupled with a wind wave model, retrievals of wind vector can be performed using a forward model approach. The surface waves play a significant role in nearshore ecosystems, affecting sediment resuspension, biomass production, and fish habitat, among others. This paper details a novel approach to estimating surface wave profiles and wind vectors using the passive, bistatic radar receiver aboard CYGNSS. The first ever retrieval of wind vector and wave height of an inland water body using spaceborne GNSS-R will be shown using raw signals recorded onboard CYGNSS.

The science payload on each spacecraft in the CYGNSS constellation is a GNSS-R receiver and antennas designed to receive GPS L1 signals scattered from the Earth surface. The constellation was launched on 15 Dec 2016 and the GNSS-R instruments continue to operate successfully. A next generation version of the receivers and antennas is in development which adds significant measurement capabilities that are expected to enhance the resolution, precision and coverage of current CYGNSS science data products as well as enable some new ones.

The effective isotropic radiated power (EIRP) of the Global Positioning System (GPS) determines the power incident on the Earth surface. It is critical to the CYGNSS mission's Level 1 calibration of normalized bistatic radar cross section (NBRCS). This paper reports a dynamic EIRP calibration algorithm that uses the CYGNSS direct signal to correct the GPS EIRP in the direction to the specular reflection point. This approach can instantaneously detect any transmit power fluctuation in all GPS transmitters and any change of the receiver system gain, and then automatically applied to correct the science measurement. It also helps mitigate the error caused by the azimuthal asymmetry of the GPS antenna gain pattern without knowing the exact yaw attitude of the GPS satellite. The dynamic EIRP calibration algorithm brings back flagged observations from the Block IIF (~37% of the entire dataset) to the CYGNSS standard science data products. It will also help improve the accuracy of Level 2 wind speed retrieval.

Spaceborne GNSS reflectometry has shown ability to observe the global inland water distribution. It allows generating dynamic maps of rivers, wetlands and inundations using the large variation in the received power while the ground track crosses those objects. Here, we analyze the change of the reflected signal's power and coherence due to surface roughness and cover (ice) observed in the CYGNSS delay-Doppler maps for Qinghai Lake, China. It is shown that a significant attenuation of the reflected coherent signal and emergence of the diffuse component occurs due to wind-generated surface waves. The comparable attenuation effect of the coherent component is observed in the case of the frozen lake. It takes place due to the lower value of the average Fresnel reflection coefficient of ice. A similar effect may occur for reflections from wetlands, when open water and water covered by vegetation could produce comparable reflected powers, however, due to different mechanisms. Understanding the relative scattering characteristics of wetlands in contrast with rougher bodies such as lakes is important for the development of algorithms to detect their dynamic changes.

Ocean surface altimetry with GNSS reflectometry (GNSS-R) has the potential to improve the observation and retrieval of mesoscale ocean current flows by increasing the spatial density of ocean surface observations. The leading challenges in current GNSS-R altimetry investigations include precise delay retracking, correction of ionospheric effects, and spacecraft receiver positioning. Here, we present improved methods to account for these challenges. A reflection-model-based approach is presented for delay retracking that uses simulated delay-Doppler maps (DDMs) to retrieve the specular delay from measured DDMs. Global ionosphere maps are used to estimate the group delay effect along the direct and reflection paths. Precise orbit determination techniques are used to improve estimates of the receiving spacecraft position and reduce systematic intersatellite biases. We analyze altimetric height retrievals from two cases, strongly coherent or diffuse reflections. We study the residual systematic error signals with a focus on understanding the errors identified above. The strong coherent observations have narrow, symmetric delay waveforms and provide higher than average signal-to-noise ratio. The DDMs of diffuse observations, originate from relatively rough ocean surfaces and have the characteristic horse-shoe shape. Only measurements from the ocean and seas surrounding Indonesia are considered as this area provides a significant number of strongly coherent reflections. More than 50 000 single-point observations and week-long averaged results are presented to quantify the noise and systematic characteristics of the retrieved surface heights.

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.

This paper presents recent work being done to produce a new GNSS Reflectometry (GNSS-R) ocean altimetry product using data from NASA's CYGNSS Mission, a constellation of 8 small satellites that measure reflected GPS signals off of the surface of the ocean. Although CYGNSS is not intended or optimized for altimetry, creation of a research product will allow assessment at the synoptic level over the life of the CYGNSS mission. The algorithms being developed here are for generation of large-scale production runs, unlike previous reports that have have examined limited sets of data. The CYGNSS Level 1 data is processed using a modified CYGNSS End-to-end Simulator (E2ES) which provides a full-forward-model waveform fit (along both delay and Doppler space) and precise delay retrieval. The delay is converted into estimated sea surface height (SSH) using auxiliary data sources for corrections, such as ionospheric, tropospheric, tidal, orbital and instrument. The resulting data product will enable thorough characterization of altimetry accuracy and remaining error sources.

Spaceborne GNSS Reflectometry (GNSS-R) measurements have shown strong coherent scattering over inland waters. It has been recognized that GNSS-R could be utilized for monitoring the global surface water distribution by making dynamic maps of wetlands as well as rapid response to flood events. Using the strength of the reflected signals, one can make maps that reveal the presence of water over land. In this paper, we used simulations to analyze the accuracy of these maps. The CYGNSS End-to-end Simulator (E2ES) was extended to include coherent scattering in the heterogeneous scenes where the region around the specular point is composed of both land and water in complex geometries. The simulation is then used to evaluate the accuracy of a simple fractional water in footprint approach to mapping wetland extent. We find that scattering from outside the first Fresnel zone and CYGNSS measurement processing effects significantly impact the accuracy of this approach. However, the accuracy can be improved by combining multiple measurements into a gridded map.

Level 1 calibration of the Cyclone Global Navigation Satellite System (CYGNSS) measurements requires an accurate estimate of the effective isotropic radiated power (EIRP) of the GPS transmitter in the direction of specular reflection. Variable transmit power by numerous Block IIF and IIR-M GPS space vehicles was observed due to their flex power mode. GPS antenna gain patterns feature azimuthal asymmetry, further complicating EIRP estimation. As a result, all Block IIF observations by CYGNSS are flagged and not used to measure ocean winds. A new (version 3.0) Level 1 calibration algorithm is developed which uses measurements by the direct (zenith) antenna to estimate the specular GPS EIRP used to calculate the bistatic radar cross section (BRCS) of the ocean surface. Direct signal measurements are used to estimate GPS transmitter EIRP in the direction of the CYGNSS spacecraft. By applying corrections to the direct signal EIRP, it is possible to estimate the GPS EIRP in the direction of the specular reflection point. This real-time EIRP calibration algorithm instantaneously detects and corrects power fluctuations in all GPS block transmitters and significantly reduces errors due to the GPS antenna gain azimuthal asymmetry. It also allows observations with Block IIF transmitters (approximately 37% of the entire dataset) to be included in the standard data products.

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.

Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) measurements of ocean winds present a challenge because the surface wind speed cannot be assumed homogeneous over the large glistening zone observable from orbit. The 25-km resolution requirement of the Cyclone GNSS (CYGNSS) mission limits wind speed retrievals to using only a small fraction of the delay-Doppler map (DDM) near the specular point. This paper presents a new method to invert a larger portion of the DDM and estimate the wind field within a swath defined by the maximum delay. An extended Kalman filter (EKF) is applied to combine a series of DDMs and estimates the wind speed on a uniformly gridded ocean surface exploiting the large overlap between sequential looks. Wind retrievals at the specular point using simulated data generated using wind fields from two hurricanes (Danielle and Earl, 2010) were found to meet the CYGNSS measurement requirements (2 m/s for U20 m/s) and perform better than a typical single-point observable. Wind retrievals were also found to meet these requirements below 20 m/s within a 90-km swath and meet them for hurricane-force winds ($17 \times 11$) DDM, demonstrating benefits of sequential processing within a limited data budget. Delay-Doppler ambiguities introduced noticeable artifacts in circumstances where the wind varies asymmetrically within the observed ($90\times 90$km) surface area but did not appear to affect specular point wind retrievals.

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.

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.

Recent results from CYGNSS measurements over land show the importance of coherent scattering. It is envisioned that future GNSS-R instruments will have the ability to separate and detect coherent scattering and downlink complex-valued coherent DDM measurements. This additional information will allow carrier phase altimetry, the separation of coherent and non-coherent scattered power, and the evaluation of geo-physical phenomena at along-track resolutions 10x greater than current spaceborne instruments, such as TDS-1 or CYGNSS. In this paper, we will present a prospective design for the on-board detection of coherent reflections. We also investigate how to achieve enhanced along-track resolution.

The CYGNSS mission is a new GNSS-R ocean remote sensing constellation of eight small spacecraft. The measurements from CYGNSS allow for the first time a large, densely sampled, and calibrated GNSS-R dataset to be used for ocean surface altimetry. Re-tracking of the reflected signal correlation waveform is one of the most significant performance limiting components of ocean altimetry retrievals. This work demonstrates the use of empirical methods and physical scattering delay/delay-Doppler waveform models, fit to the measured correlation functions in a least-squares sense, to retrieve the specular reflection delay. We examine the performance of waveform modelling methods as compared to single-point re-tracking methods for the first time with a spaceborne dataset. Particular attention is given to the presence of narrow waveforms in the data set, indicative of coherent, rather than purely diffuse reflection. Re-tracking performance is quantified with statistics of the accuracy and precision and examples are presented for returns demonstrating both diffuse and coherent characteristics.

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.

The current generation of spaceborne GNSS-R instruments, such as CYGNSS, utilize only narrowband GPS Ll CIA-coded signals at a 1575.42 MHz center frequency. A next-generation instrument being developed will also support Galileo E1bc signals as well as wideband GPS L5 and Galileo E5 signals. The additional bandwidth in the L5/E5 band should significantly improve the spatial resolution and range accuracy of measured reflections and the corresponding scientific products. In the proposed implementation, these reflection measurements will be made using a locally generated reference signal (i.e. conventional GNSS-R). However, the use of wideband, high-spatial-resolution, high-range-accuracy measurements are often cited as a benefit of the interferometric GNSS-R approach. In this work, we develop a simulator to compare the performance of the two approaches, both in terms of measurement quality and implementation complexity.

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 Cyclone Global Navigation Satellite System (CYGNSS) mission was designed to study hurricane intensification by measuring wind speeds in tropical cyclones. However, the delay-Doppler maps (DDM) that are produced can be used to estimate the sea surface height (SSH) at the specular reflection point on the ocean surface. Proof-of-concept studies that DDMs are suitable to solve for SSH have been recently reported (Clarizia et al., 2016; Mashburn et al., 2018), based on data acquired by the demonstration satellite experiment Tech Demo Sat -1 (TDS-1) carrying a GNSS-R receiver similar to the ones onboard CYGNSS. Although the precision of each 1-sec averaged SSH is considerably lower than that of the existing satellite altimeters, by virtue of the dense coverage and frequent revisit time exhibited by the constellation of 8 microsats, the error may be smoothed down considerably by optimal interpolation (Li et al., 2016). Hence the CYGNSS dataset presents a potential opportunity to sample the tropical oceans, and investigate the sensitivity of the SSH measurements to mesoscale eddies.

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.

GNSS-R (Global Navigation Satellite System Reflectometry) is being increasingly used in Earth remote sensing applications; however, up until now, dual-polarized data from spaceborne instruments has not been available. Recently, the radar aboard the SMAP satellite has provided raw received signal data on the GPS L2C frequency band. This data is simultaneously received from two high-gain (36 dBi), dual-polarized channels with excellent cross-polarization isolation. It is currently the only instrument capable of providing high-quality, dual-polarized GNSS-R measurements from space and represents a unique opportunity to study polarimetric scattering properties of geophysical phenomena. This paper presents dual-polarized GPS L2C reflection measurements made using the SMAP data over different ocean (including tropical cyclones) and land surface types. A full, high-fidelity forward SMAP GNSS-R model has been developed and applied in order to interpret scattering properties from the complex Delay-Doppler Map (DDM) data.

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.

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.

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.

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 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.

This paper reviews Global Navigation Satellite Systems (GNSS) antennas and arrays for robust coverage in presence of interference signals with a focus on antenna design aspects. A number of small antenna designs are presented that cover multiple current and future GNSS frequency bands (1150-1610 MHz) with sizes as small as 1 in (25 mm) in diameter. Several arrays are presented with a size as small as 3.5 in (8.9 cm) in diameter and approximately 0.5 in (13 mm) thick as compared to commercially available apertures 14 in (35.6 cm) and 5.5 in (14.0 cm) in diameter. These small arrays are shown to satisfy the gain requirements of GNSS receivers while simultaneously offering four to six antenna elements for adaptive interference suppression.

This paper develops and characterizes the algorithms used to generate the Level 1 (L1) science data products of the Cyclone Global Navigation Satellite System (CYGNSS) mission. The L1 calibration consists of two parts: the Level 1a (L1a) calibration converts the raw Level 0 delay-Doppler maps (DDMs) of processed counts into received power in units of watts. The L1a DDMs are then converted to Level 1b DDMs of bistatic radar cross section values by unwrapping the forward scattering model and generating two additional DDMs: one of unnormalized bistatic radar cross section values (in units of square meters) and a second of bin-by-bin effective scattering areas. The L1 data products are generated in such a way as to allow for flexible processing of variable areas of the DDM (which correspond to different regions on the surface). The application of the L1 data products to the generation of input observables for the CYGNSS Level 2 (L2) wind retrievals is also presented. This includes a demonstration of using only near-specular DDM bins to calculate a normalized bistatic radar cross section (unitless, i.e., m2/m2) over a subset of DDM pixels, or DDM area. Additionally, an extensive term-by-term error analysis has been performed using this example extent of the DDM to help quantify the sensitivity of the L1 calibration as a function of key internal instrument and external parameters in the near-specular region.

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.