This work introduces the ongoing initiatives by the "RFI in Remote Sensing Working Group" within the IEEE Standards Association. The Working Group is taking the lead in standardizing the evaluation of radio frequency interference (RFI) impact on spaceborne microwave remote sensing. This standardization effort aims to enhance the monitoring of RFI and improve the effectiveness of sharing information related to it. It is developing a standard titled "P4006 Standard for Remote Sensing Frequency Band Radio Frequency Interference (RFI) Impact Assessment". This paper presents these efforts and highlights the recent activities undertaken by this working group.

Radio Frequency Interference (RFI) has long been a problem for L-band microwave radiometers, such as SMOS, Aquarius and SMAP. This paper reports on the activities performed by the SMAP RFI team to identify and report persistent sources with the aim of decreasing global RFI occurrences at L-band.

The paper presents a commercially available, low-power digital spectrometer Application Specific Integrated Circuit (ASIC). We describe the ASIC architecture, its implementation aspects as well as board level spectrometer solutions. ASIC application examples as well as testing data are also presented. Data show adequate performance parameters for spectroradiometer applications at exceptionally low Size, Weight and Power (SWaP), compared to solutions based on off-the-shelf components. The ASIC development was funded through several NASA Small Business Innovative Research (SBIR) program awards.

We present a comprehensive Earth Planetary Boundary Layer temperature and water vapor retrieval improvement demonstration by the use of hyperspectral microwave measurements. Our results indicate that the use of a hyperspectral sampling in the oxygen and water vapor sounding lines alone provides significant improvements in the lower and free tropospheric thermodynamic fields (up to 40%), when compared against the program of record (i.e., the Advanced Technology Microwave Sounder, ATMS). Our experiments also demonstrate the essential role played by extending the coverage in the so called spectral window regions, leading to an overall PBL temperature and water vapor improvement of up to 50%.

Even when radio frequency interference (RFI) is detected, very little is known about the sources of the interference. More information about the sources would facilitate the design of systems to deal with the interference. Reporting of interference by the RFI teams for SMAP and SMOS through international channels has resulted in a decrease in RFI and identification of several sources. Two such cases that have been identified in the USA and are reported here.

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.

This paper presents an overview of the Hyperspectral Microwave Photonic Instrument (HyMPI), a 2021 NASA Instrument Incubation Proposal funded project aimed at developing the very first hyperspectral microwave sensor to augment thermodynamic sounding capability from space, with a focus on the Earth's Planetary Boundary Layer. This research responds to the recommendation expressed in the 2018 National Academies of Sciences decadal survey to accelerate the readiness of high-priority PBL observables not feasible for cost-effective spaceflight in 2017–2027. This paper provides an overview on HyMPI's design, configured as the objective instrument concept needed to fly in the future PBL mission and presents preliminary trade studies aim at demonstrating HyMPI's enhanced thermodynamic sounding skill in the Earth's Planetary Boundary Layer over conventional microwave sounders from the current Program of Record.

We present an overview of the Hyperspectral Microwave Photonic Instrument (HyMPI), a NASA Instrument Incubation Proposal funded research project aimed at developing a hyperspectral microwave instrument intended for enhanced remote sensing of atmospheric temperature and water vapor from space. This paper provides preliminary results on HyMPI's spectral and noise characteristics and a preliminary demonstration of its enhanced water vapor sensitivity and vertical resolution, with a particular focus on the Earth's Planetary Boundary Layer.

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.

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.

A proof-of-concept experiment has demonstrated that wideband (400 MHz) signals of opportunity (SoOp) transmitted in K- and Ku-bands from geostationary satellites can be used for coastal altimetry. An essential finding from this experiment is that the full broadcast spectrum consisting of multiple digital channels can be processed as a single wideband signal source. An established error model for Global Navigation Satellite System interferometric altimetry was shown to accurately represent the sea surface height (SSH) retrievals when evaluated using the full bandwidth. This experiment was conducted over a 72-h period at Platform Harvest off the Pacific Coast. Colocated tide gauge and LiDAR measurements were used as in situ data. Two anomalies were observed in the experiment: 1) multiple peaks in the cross correlation waveform from one polarization of Ku-band frequency and 2) decrease in signal-to-noise ratio from loss of a data channel. When the instances of multiple peaks were eliminated and the equivalent bandwidth recomputed using only the active channels, SSH error from these cases agreed well with the model prediction. Application of SoOp wideband altimetry will, therefore, require a monitoring capability to identify changes in the transmission spectrum, total power, and waveform shape, for quality control and setting an appropriate observation error covariance. Measurement precision from a satellite receiver is predicted to be between 4 and 6 cm using the error model. SoOp altimetry with these signals may improve coastal measurements and increase the sampling and revisit rate through the use of a constellation of small satellites.

Microwave radiometers measure weak thermal emission from the Earth, which is broadband in nature. Radio frequency interference (RFI) originates from active transmitters and is typically narrow band, directional, and continuous or intermittent. The Global Precipitation Measurement (GPM) Microwave Imager (GMI) has seen RFI caused by ocean reflections from direct broadcast and communication satellites in the shared 18.7-GHz allocated band. This paper focuses on the use of a complex signal kurtosis algorithm to detect direct broadcast satellite (DBS) signals at 18.7 GHz. An experiment was conducted in August 2017 at the Harvest oil platform, located about 10 km off the coast of central California. Data were collected for direct and ocean reflected DBS transmissions in the K- and Ku-bands from a commercial geostationary satellite. Results are presented for the complex kurtosis performance for a five-channel quadrature phase-shift keying (QPSK) signal versus the seven-channel case. As the spectrum becomes more occupied, detector performance decreases. Filtering of RFI in the fully occupied spectrum is very difficult, and detection using the complex kurtosis detector is only possible for very large interference-to-noise ratio (INR) values at -5 dB and higher. This corresponds to over 100 K in a real system such as GMI; therefore, other detection approaches might be more appropriate.

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.

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 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.

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 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.

Radio Frequency Interference (RFI) is a threat to passive microwave measurements and if undetected, can corrupt science retrievals. The sparse component analysis (SCA) for blind source separation has been investigated to detect RFI in microwave radiometer data. Various techniques using SCA have been simulated to determine detection performance with continuous wave (CW) RFI.

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.

Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interferece-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.

Coastal altimetry plays a prominent role in measuring the total water-level envelope directly, and is one of the key measurements required by storm surge applications and services. It can also provide important information about the wave field, leading to development of more realistic wave models and therefore improving forecasts of wave setup and overtopping processes. Satellite altimeters have a long history of mapping the variability of the Earth's open ocean. However, this is not the case for coastal areas because of the limitations of technology and difficulties in processing and interpretation of data near coastal surface (due land contamination and rapid variations due to tides and atmospheric effects). There is, therefore, a need for more accurate Sea Surface Height (SSH) near coastal areas. Bistatic altimetry using signals of opportunity (SoOp) (e.g. digital communication signals) may provide additional measurements in coastal areas through oblique incidence angles and high bandwidth (400 MHz). In this study, we investigate the capabilities of SoOp technique for coastal altimetry from spaceborne platforms.

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.

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 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.

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.

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.

RFI is a persistent and growing problem experienced by spaceborne microwave radiometers. Recent missions such as SMOS, SMAP, and GPM have all detected RFI in L, C, X, and K bands. To proactively deal with this issue, microwave radiometers must include digital back-end processors that generate data products that facilitate the detection and excision of RFI from desired brightness temperature measurements. The wideband digital signal processing testbed is a platform that allows rapid development of various RFI detection and mitigation algorithms using digital hardware akin to that which might be used for final spaceflight implementation. On it, we evaluate an improved version of the SMAP RFI Digital Signal Processor (DSP) that utilizes the new complex signal kurtosis algorithm as opposed to the real signal kurtosis that is used on the SMAP radiometer. In addition, we show how we scale the DSP to operate at 8.3 times the bandwidth of the SMAP radiometer for operation in K-band.

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.

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).

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.

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.

The presence of anthropogenic RFI is expected to adversely impact soil moisture measurement by NASA's Soil Moisture Active Passive mission. The digital signal processing approach and preliminary design for detecting and mitigating this RFI is presented in this paper. This approach is largely based upon the work of Johnson and Ruf.

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.

A double detector (DD) for radio-frequency interference (RFI) in microwave radiometers is demonstrated in theory and practice. The detector is based on the principle of using kurtosis to detect the presence of non-Gaussian signals and is shown to approximate the kurtosis of input. Theoretical response to continuous wave and pulsed RFI is derived and tested in two experiments. The DD hardware comprises two microwave detectors, two integrator-amplifiers, and a wideband video amplifier. The technique is compatible with existing direct-detection radiometer designs and desirable for applications requiring low technological risk.