Geolocation of the radiometer footprint in scanning instruments such as SMAP (Soil Moisture Active Passive) has been successfully demonstrated using the change in antenna temperature as the radiometer scans across land/water boundaries (coastlines). This measurement provides the distance of the footprint from the nominal coastline, but it does not provide information about the error in look angle and azimuth of the antenna boresight vector needed to correct the geolocation error. A method for doing this is reported using fore and aft crossings of the boundary. The approach is demonstrated using the SMAP radiometer simulator and then applied to SMAP data over the west coast of Madagascar. The error estimates of 0.3° for the look angle and 0.15° for azimuth are consistent with independent estimates.

The Soil Moisture Active Passive (SMAP) mission was launched on 31 st January 2015 in a 6 AM/6 PM sun-synchronous orbit at 685 km altitude to measure soil moisture and free/thaw globally [1]. A radar (active) and a radiometer (passive) are onboard, and they share a single feedhorn and mesh reflector. The antenna pointing was calibrated by the radar and the result is applied to the radiometer. Because the two instruments work at different frequencies, the antenna pointing for the two instruments are slightly different. Calibration of the radiometer antenna pointing is necessary for improving the water-body correction used in the soil moisture retrieval and improving the ocean surface incidence accuracy needed in the retrieval of sea surface salinity (SSS). The calibration activity has been performed and the result will be presented.

Polarimetric microwave radiometers such as SMAP are capable of measuring the fourth Stokes parameter in brightness temperature over the Earth surface. The value of this parameter is normally small but exhibits sharp spikes when the scene includes large differences in emission from the surface, such as occur at land/water boundaries. In this manuscript, it is shown that these spikes can be used to accurately locate coastlines with potential application to geolocation in passive microwave remote sensing from space. Examples are presented using the L-band radiometer on SMAP, first with theory using calculations with the SMAP antenna pattern and orbit and then with SMAP measurements of the fourth Stokes parameter over Madagascar. Using the SMAP data, the coastline is located with a standard deviation less than 2 km. The results are consistent with the conventional approach used for geolocation of the SMAP radiometer footprint.

Over the years, a fixed window for smoothing radiometer cold-space and warm-load counts and processing brightness temperature in calibration has been used for all microwave sounders at EUMETSAT and NOAA. Although this practice is based on ground tests and legacy satellites, it remains unclear if this empirical parameter is optimal for in-orbit radiometers, as the space environment is different from the ground and radiometers may drift. We found that the fixed window is not optimal and leads to large noise.We have developed an adaptive window that accommodates channel differences and temporal changes in hardware. Our method has reduced noise by as much as 50% for 183 GHz channels of MetOp-C MHS. We observed temporal jumps and shifts in counts, gain and noise of 89 and 190 GHz, and accordingly, the adaptive window can adjust to reduce such an impact. Further analyses reveal that 1/fnoise plays an important role for determining the adaptive window. 1/fnoise is non-stationary and gives rise to the fluctuation of counts and gain. As a result, for channels with large 1/fnoise a short window should be used to mitigate the fluctuation. Our study suggests an adaptive method has advantages over the fixed method for considering channel differences and timevarying noise.

The Soil Moisture Active Passive (SMAP) mission was launched on 31stJanuary 2015 in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude to measure soil moisture and free/thaw globally [1]. The passive instrument of SMAP is a fully polarimetric L-band radiometer (1.4GHz) operating with a bandwidth of 24MHz. The radiometer uses a combination of noise-diodes and Dicke-loads for internal calibration with a design similar to that used by the Aquarius or Jason series radiometers [2], [3]. Pre-launch calibration activities had been performed since 2012 on the engineering model of the radiometer. Post-launch calibration activities have been performed to fine-tune and validate the results from the pre-launch calibration. The major calibration activities and lessons learned in the past 8 years will be described in the following sessions.

Modern multi-band radiometer imagers are designed trading spatial resolution, spectral coverage, and surface sampling characteristics to optimize science return. In this process, trades must be made to usually under-sample the Earth scene. Care is taken to obtain contiguous 3-dB edge-to-edge coverage, but even so, such a design still aliases high spatial frequency content in the image.

The SMAP L-band microwave radiometer is in its extended mission of measuring soil moisture and freeze/thaw state globally for quantifying the water and carbon cycles. Instrument behavior has been stable over the past 4 years and 9 months. With the concurrent calibration of the internal calibration parameters and the antenna gain after estimating reflector emissivity, the SMAP radiometer measurements exhibit 0.1 K (rms) stability and nearly zero biases over the averaged global ocean and monthly Cold Sky views. The data (version 4) were released to the public in 2018 for various science activities. Now the radiometer data are under revisit to improve the absolute radiometric calibration and reduce calibration drift. Several approaches are investigated to obtain the optimal solution. In addition, the correction to the radiometer measurement when the SMAP radar transmitter was operational will also be revisited for the next data release. The performances of the calibration revisit and Radio-Frequency Interference (RFI) trends will be presented as well.

The Soil Moisture Active Passive (SMAP) mission, launched on January 31, 2015, has completed its primary 3-year mission and is currently in its extended mission. Although operation occurs within the protected frequency allocation of 1400-1427 MHz, the SMAP radiometer is impacted by radio frequency interference (RFI). The radiometer was designed to provide detection and filtering of RFI in order to meet error budget requirements. A time series algorithm was developed to monitor, detect and report the changing environment with the objective of detecting new RFI sources as well as existing persistent sources. The detection of sources are used in RFI reporting to NASA spectrum management with the hope that interfering sources will be turned off by the necessary administrations.

The SMAP L-band microwave radiometer has completed its 3-year primary mission of measuring soil moisture and freeze/thaw state globally for quantifying the water and carbon cyclces. Instrument behavior is stable over the past 3 years and 9 months. With the concurrent calibration of the internal calibration parameters and the antenna gain after estimating reflector emissivity, the SMAP radiometer measurements exhibit 0.1 K (rms) stability and nearly zero biases over the averaged global ocean and monthly Cold Sky views. The data (version 4) was released to the public in 2018 for various science activities. Now the radiometer is under revisit to improve the absolute radiometric calibration and reduce calibration drift. Several approaches are being used to obtain the optimal solution. In addition, the correction to the impact on the radiometer measurement when the SMAP radar transmitter was on will also be revisited for next data release.

Multiband passive microwave imagery in X to W Bands has a nearly 40-year history of utilization for measurement of multiple geophysical parameters (e.g., precipitation rate, ocean surface wind speed, sea ice concentration, and land surface temperature). Spatial resolution is limited by aperture size, and although aperture sizes have grown to 1-2 meters, current capability will not meet future spatial resolution needs. As aperture size increases, new antenna feed techniques are needed to maintain contiguous coverage and obtain Nyquist sampling. Here we apply the correlator array-fed radiometer architecture adapted from radio astronomy and show how it can meet emerging needs. Simulation results of a 0.8-m, 36.5-GHz, array-fed reflector (equivalent to 20 meters at 1.41 GHz) show the feasibility of creating multiple over-lapping beams.

The Soil Moisture Active Passive (SMAP) mission was designed to acquire and combine L-band radar and radiometer measurements for the estimation of soil moisture with 4% volumetric accuracy away from coastal zones. In regions near the coast or near inland bodies of water, the SMAP footprint contains land and water, resulting in errors in the soil moisture estimation. In this paper, we address the effort to extract the brightness temperature related to the land fraction or water fraction (depending on the center of the footprint location) from the affected SMAP measurements. We evaluate the performance of our algorithm over simulated data. We then show results over real data. The new SMAP upgraded product is expected to be delivered on April 2018.

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 SMAP mission was designed to measure soil moisture globally for quantifying the water and carbon cyclces. The Brightness Temperature (TB) measurement by the SMAP L-band radiometer over ocean is also used for Sea Surface Salinity (SSS) retrieval. Considering the requirement of the uncertainty in the L-band TB measurement for SSS retrieval, the reflected galaxy correction is to be upgraded by using wind speed dependent galactic TB maps (the cosmic microwave background is included) for the radiometer TB data product (version 4) which is expected to be released in the summer 2018. We address the development of the galactic TB maps. In addition, a correction offset to the modeled ocean radiometric observation for horizontal polarization is described.

The SMAP microwave radiometer will see its third anniversary of operations on March 31, 2018. Instrument behavior is stable over 33 months of operation to date. The physical temperature of the internal calibration sources varies 0.5°C. The bias current of the noise source drifted by less than 0.1%. The avalanche breakdown voltage of the noise diode shows 0.01% seasonal variation. The average NEDT of the radiometer has maintained a stable 1-K value over the period. This stable behavior of the hardware is critical for the consistent calibration. The reflector emissivity was re-estimated using on-orbit data. Use of the new value nearly eliminates bias caused by solar eclipse during the southern hemisphere winter. The radiometer data were recalibrated using, as earlier, global ocean and cold sky views with additional ocean and land views at nadir incidence. The Version 4 recalibrated data exhibit 0.1-K RMS stability over average global ocean and monthly cold-sky views.

In this paper we summarize the effort to enhance the SMAP radiometer data. The applied technique is based on the Backus-Gilbert theory which is the classical estimation method in microwave radiometry. We show details of our implementation and summarize the assessment of the SMAP L1C_TB_E product.

The Soil Moisture Active Passive (SMAP) mission was launched on 31stJanuary 2015 in a 6 AM/6 PM sun-synchronous orbit at 685 km altitude to measure soil moisture and free/thaw globally [1]. The passive instrument of SMAP is a fully polarimetric L-band radiometer (1.4GHz) operating with a bandwidth of 24MHz. The radiometer uses a combination of noise-diodes and Dicke-loads for internal calibration with a design similar to that used by the Aquarius or Jason series radiometers [3]. The SMAP digital backend back-end enables implementation of advanced Radio Frequency Interference (RFI) detection and mitigation algorithms for corrupted L-band measurements [6]. The radiometer uncalibrated raw counts are converted to Level 1B antenna temperatures and brightness temperature (TB) values [2]. These TB values are used with other ancillary data to retrieve soil-moisture products on a 40km global grid. The error requirement for the SMAP radiometer is 1.3K and calibration drift is less than 0.4 K/month to measure soil-moisture with volumetric fraction uncertainty of less than 0.04 m3/m3.

Soil moisture impacts exchanges of water, energy and carbon fluxes between the land surface and the atmosphere. Passive microwave remote sensing at L-band can capture spatial and temporal patterns of soil moisture in the landscape. Both ESA and NASA have launched L-band radiometers, in the form of the SMOS and SMAP satellites respectively, to monitor soil moisture globally, every 3-day at about 40 km resolution. However, their coarse scale restricts the range of applications. While SMAP included an L-band radar to downscale the radiometer soil moisture to 9 km, the radar failed after 3 months and this initial approach is not applicable to developing a consistent long term soil moisture product across the two missions anymore. Existing optical-, radiometer-, and oversampling-based downscaling methods could be an alternative to the radar-based approach for delivering such data. Nevertheless, retrieval of a consistent high resolution soil moisture product remains a challenge, and there has been no comprehensive intercomparison of the alternate approaches. This research undertakes an assessment of the different downscaling approaches using the SMAPEx-4 field campaign data.

The Soil Moisture Active/Passive (SMAP) microwave radiometer is a fully polarimetric L-band radiometer flown on the SMAP satellite in a 6 a.m./6 p.m. sun-synchronous orbit at 685-km altitude. Since April 2015, the radiometer has been under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods, including the SMAP L1B TA2TB [from antenna temperature (TA) to the Earth's surface brightness temperature (TB)] algorithm and TA forward models, are outlined, and validation approaches for calibration stability/quality are described in this paper, including future work. Results show that the current radiometer L1B data product (version 3) satisfies its requirements (uncertainty <;1.3 K and calibration drift <;0.4 K/months, and geolocation uncertainty <;4 km) although there are biases in TA over cold sky and in TB comparing with the Soil Moisture and Ocean Salinity TB v620 data products.

The Soil Moisture Active-Passive (SMAP) L-band microwave radiometer is a conical scanning instrument designed to measure soil moisture with 4% volumetric accuracy at 40-km spatial resolution. SMAP is NASA's first Earth Systematic Mission developed in response to its first Earth science decadal survey. Here, the design is reviewed and the results of its first year on orbit are presented. Unique features of the radiometer include a large 6-m rotating reflector, fully polarimetric radiometer receiver with internal calibration, and radio-frequency interference detection and filtering hardware. The radiometer electronics are thermally controlled to achieve good radiometric stability. Analyses of on-orbit results indicate that the electrical and thermal characteristics of the electronics and internal calibration sources are very stable and promote excellent gain stability. Radiometer NEDT1 MHz and 1/f noise rising at longer time scales fully captured by the internal calibration scheme. Results from sky observations and global swath imagery of all four Stokes antenna temperatures indicate that the instrument is operating as expected.

We present an assessment of the precision of the pointing and geolocation of the SMAP (Soil Moisture Actice and Passive) satellite's passive instrument, based on the first year of on-orbit operation. The SMAP radiometer has an effective footprint of 39-by-47 km (HPBW) and a geolocation requirement of 4 km.

In this paper we summarize the effort to enhance the resolution of SMAP radiometer data. The SMAP radiometer sampling of the Earth surface provides overlapping measurements along scan and along track. The oversampling combined with the given antenna gain function allows reconstruction of the scene with improved resolution. The applied technique is based on the Backus-Gilbert optimum interpolation theory, which is the classical inversion method in microwave radiometry. The results shown in this paper are based on the simulated SMAP measurements and are applicable to the real SMAP radiometer measurements.

In this paper we discuss the steps taken for the calibration and validation of the Soil Moisture Active Passive (SMAP) L-band radiometer. We discuss the use of multiple vicarious sources such as the global ocean mean and celestial cold-sky emissions along with various spacecraft maneuvers to calibrate out gain, offset, antenna pattern of the radiometer. We present initial validation comparison of SMAP brightness temperatures with other L-band missions.

The radiometer Subband calibration and calibration drift correction have been successfully used in the released radiometer L1B data product. Although their performances satisfy the requirements, they are still under continuing analysis to find their remaining uncertainty. The progress will be presented besides the current performance.

Faraday rotation is an important issue for remote sensing of parameters such as soil moisture and ocean salinity, which are best done at low microwave frequency (e.g., L-band). Modern instruments such as the radiometer on the Soil Moisture and Ocean Salinity (SMOS) satellite and the Aquarius radiometers include polarimetric radiometer channels specifically to implement a correction for Faraday rotation. This works well over ocean, but it is known that over inhomogeneous scenes, such as a land/water mixture, significant errors can occur. This is a particularly important issue for the newest L-band sensor in space, the radiometer on the Soil Moisture Active Passive (SMAP) satellite, where the goal is remote sensing over land (soil moisture) and where the conical scan induces rapid variation in Faraday rotation. Analysis is presented here of the issues associated with retrieving Faraday rotation using the SMAP geometry and antenna pattern. It is shown that, in addition to scenes with a mixture of land and water, scenes with significant vegetation canopy are also associated with large errors in the retrieved Faraday rotation. Examples from the SMAP radiometer support the analysis.

Aquarius is a space-borne 3-beam L-band microwave instrument with its radiometer measuring sea surface salinity and its scatterometer providing ocean roughness corrections for better retrieval. Since polarized signals are used in both salinity and surface wind retrievals, Faraday rotation correction is an important step in calculating both radiometer and scatterometer ocean surface signals. In current ground processing algorithm, data version 3.0, scatterometer Faraday rotation is derived from predictions based on TEC inputs while radiometer Faraday rotation is computed using second and third stokes measurements. Analysis shows general agreement between these two values for all three beams. Discrepancies reside along certain geolocations and vary seasonally.

The Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions provide Level-1 brightness temperature (Tb) observations that are used for global soil moisture estimation. However, the nature of these Tb data differs: the SMOS Tb observations contain atmospheric and select reflected extraterrestrial (“Sky”) radiation, whereas the SMAP Tb data are corrected for these contributions, using auxiliary near-surface information. Furthermore, the SMOS Tb observations are multiangular, whereas the SMAP Tb is measured at 40° incidence angle only. This letter discusses how SMOS Tb, SMAP Tb, and radiative transfer modeling components can be aligned in order to enable a seamless exchange of SMOS and SMAP Tb data in soil moisture retrieval and assimilation systems. The aggregated contribution of the atmospheric and reflected Sky radiation is, on average, about 1 K for horizontally polarized Tb and 0.5 K for vertically polarized Tb at 40° incidence angle, but local and short-term values regularly exceed 5 K.

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.

A simplified atmospheric radiative transfer model at L-band has been developed for the Soil Moisture Active/Passive (SMAP) forward brightness temperature (level 1) simulator. The upwelling and downwelling brightness temperatures and the total loss factor of the atmosphere are modeled as polynomial functions of pressure, temperature, and water vapor density near the Earth's surface, as well as incidence angle. The model has been developed and verified by using global radiosonde data, and the model error is within the 0.1 K error budget (atmosphere portion) of the SMAP brightness temperature (Level 1B) product.

SMAP is one of four Tier-1 missions recommended by the National Research Council's Committee on Earth Science and Applications from Space [1]. The mission consists of a spacecraft with two instruments: an active L-band 1.26 GHz synthetic aperture radar and a passive L-band radiometer that operates in the 1.400 to 1.427 GHz microwave band. The goal of the mission is to use data derived from both instruments to construct high-resolution, high-accuracy global maps of soil moisture and freeze/thaw states over a 3 year mission duration. The SMAP radiometer has an entirely digital back-end processor that builds upon the findings by Misra et. al. [2], [3] for its digital signal processing (DSP) and radio frequency interference (RFI) mitigation. The implementation of this radiometer is currently under way and the mission is scheduled to launch in 2015. This paper summarizes the design and performance results of the RDE engineering test unit (ETU).

The covariance statistics of measurements by a fully polarimetric microwave radiometer are derived using a fundamental noise-theoretic approach. Previous published derivations of a similar nature have only included the third Stokes brightness temperature. The results are confirmed by a series of numerical Monte Carlo simulations of the underlying radiometric measurement process. It is found that the additive noise that is present in the measurements can be correlated between polarimetric channels and that the correlation statistics will vary as a function of the polarization state of the scene under observation. General expressions are also derived for the measurement precision (the radiometric NEΔT) and the system noise temperature of the third and fourth Stokes channels. It is found that both the precision and noise temperature can also depend on the polarization state of the scene.

In this paper, a new and improved L-band version of the correlated noise calibration standard (CNCS) has been developed to aid in the characterization of polarimetric microwave radiometers. The CNCS generates a series of known polarimetric test signals using a two-channel commercial arbitrary waveform generator (AWG) and a pair of frequency-upconversion modules. When it is inserted in place of the antenna used by a radiometer-under-test (RUT), it can fully characterize the polarimetric response of the receiver portion of the RUT. Both hardware and software improvements have been made over a previous version of the CNCS. The frequency upconverters now include integral warm and cold calibration-reference targets to automatically compensate for small drifts in AWG output-signal strength. The procedure used to calibrate the RUT has been generalized to correct for nonideal characteristics of the CNCS itself. Moreover, the effects on the derived polarimetric gain matrix of impedance mismatches between the RUT, and either the CNCS or the antenna have been determined. Details of the CNCS improvements are presented. The results of an experimental demonstration of its use and of a series of validation tests of its performance are also presented.

All microwave radiometer measurements of brightness temperature (TB) include an additive noise component. With conventional linearly polarized radiometers, the variance of the noise is a well-understood function of the system temperature, the predetection bandwidth, and the integration time according to the so-called ldquoradiometer uncertainty equation.rdquo The noise has generally been considered to be uncorrelated between orthogonally polarized channels. The variance and the correlation statistics of the additive noise component of fully polarimetric radiometer measurements are derived from theoretical considerations, and the resulting relationships are experimentally verified. It is found that the noise can be correlated between polarimetric channels, and the correlation statistics will vary as a function of the polarization state of the scene under observation. For example, a strong correlation is typical between the noise in either vertically or horizontally polarizedTBand the 45 deg slant linear polarizations that are often used to derive the third StokesTB. A weak, but nonzero, correlation is also possible between the additive noise in the vertically and horizontally polarizedTB's themselves. This is a correction to the common assumption that they are uncorrelated.

A new and improved L-Band version of a programmable digital noise source has been developed to aid in the characterization of microwave radiometers. The system consists of a commercial Arbitrary Waveform Generator (AWG), “RF Head” frequency upconversion modulators with integral calibration reference sources, and a local oscillator. It is being used to evaluate the performance of two upcoming spaceborne microwave radiometers - the Aquarius polarimetric radiometer (a low earth orbiting ocean salinity mission) and the Juno microwave radiometer (a Jupiter orbiter for atmospheric sounding). For each of these radiometer evaluations, the programmable noise source can generate signals that: a) simulate the expected observations and test the radiometer’s response; and b) exercise the radiometer’s response to variations in the observations in such a way that its overall behavior can be more fully characterized.