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.

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.

Radio frequency interference (RFI) is a problem in microwave remote sensing even for sensors operating in the protected band at 1.4 GHz (L-band). Unfortunately, little is known about the sources of the interference, which complicates the design of systems to deal with it. A unique feature of the Soil Moisture Active Passive (SMAP) radiometer is that it comprises an array of tools to detect RFI, including spectral information and kurtosis in addition to the more conventional time-domain thresholding. This article reports the results of an investigation to determine if the kurtosis ($K$) can be combined with the information about the spectrum of the RFI to identify characteristics of the source of the RFI. The SMAP conical scan permits accurate location of the source of RFI resulting in a few cases where identification of the source of RFI was possible. The known sources include both radar and domestic electronics. Evidence is presented that RFI with$K < 3$is most likely to be continuous and confined to a narrow frequency (e.g., faulty electronics) and that RFI with$K >$3 and large is likely to be associated with short pulses (e.g., radar, but there are exceptions). A critical parameter in determining the magnitude of the kurtosis is the duration of the RFI relative to the integration time of the radiometer.

In this paper, we describe the attempt of the Frequency Allocation in Remote Sensing Technical Committee (FARS-TC) from the IEEE Geoscience and Remote Sensing Society (GRSS) to standardize the impact assessment of radio frequency interference (RFI) especially in the field of spaceborne remote sensing. Multiple radio services have been sharing a common radio band with remote sensing satellites, resulting in inevitable interferences between each other. In other cases, some services accidentally emit their signal to nearby frequency band. Detecting interference and locating its source is a necessary task to guarantee data integrity. Given that remote sensing satellites carry unique payloads, the effect that RFI have depends on each sensor. For this reason, the RFI impact assessments have been usually developed with one mission or application in mind.Standardizing the impact assessment of RFI will benefit to make a public identification system so that we can monitor RFI effectively. In this paper, we introduce the working group in the IEEE Standards Association named "P4006 Standard for Remote Sensing Frequency Band Radio Frequency Interference (RFI) Impact Assessment" which is handled by the IEEE GRSS FARS-TC and its recent activities.

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.

Accurate knowledge of the dielectric constant of sea water is important for remote sensing of surface parameters such as sea surface temperature (SST) and sea surface salinity (SSS). The advent of sensors in space, SMOS [1] , Aquarius [2] and SMAP [3] capable of measuring SSS motivated modern measurements [4] , [5] and modelling [5] , [6] of the dielectric constant at L-band (1.4 GHz). In the past, the range of salinity included in the data used to create these models has been restricted to values typically encountered in the open ocean (e.g., less than 40 psu). However, there are many smaller water bodies with much higher salinity. Notable examples are the Great Salt Lake in Utah with salinity on the order of 180 psu and Garabogazköl lagoon in Turkmenistan with even higher salinity. Unfortunately, existing models for the dielectric constant can’t necessarily just be extended to higher values of salinity. The problem is that the polynomials in salinity and temperature used to represent the unknown parameters in the models are not constrained outside the range of SSS and SST used to determine their coefficients. While the models for the dielectric constant may be very good within that range, outside that range they can lead to unrealistic behavior. Research is underway to develop a model that represents the dielectric constant well over the ocean and behaves well at high salinity. In preparation for possible wideband remote sensing of salinity [7] , [8] , [9] , the laboratory measurements made at 1.413 GHz [4] , [5] are being repeated at 0.707 GHz (P-band) and the plan is to include values of high salinity (50, 100, 150 psu).

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.

This paper presents an analysis of Radio Frequency Interference (RFI) in the 1.400-1.427 GHz frequency band. The study considers the sudden and strong increase of interference from a particular emitter in China that has been observed in July 2020 by radiometers from both ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's SMAP (Soil Moisture Active Passive) missions. It provides an example of the characterization of a source of RFI and illustrates the capabilities of the SMAP radiometer receiver and RFI processing incorporated in it to identify and understand interference.

The important task of deciding and revising frequency allocations at international level falls under the responsibility of the World Radiocommunication Conference (WRC) which is organized by a specialized agency of the United Nations, the Radiocommunications Sector of the International Telecommunications Union (ITU-R). A WRC is held every approximately four years for the purpose of updating the international Radio Regulations (RR). The most recent of these conferences, WRC-19, held at the end of 2019, also defined the Agenda Items for the next WRC that is scheduled to occur in 2023. Here, we review and discuss the WRC-23 Agenda Items that are likely to have the most impact on future remote sensing operations.

Radio-frequency interference (RFI) has had a detrimental effect on L-band passive observatories such as SMOS, Aquarius and SMAP. A better knowledge of the characteristics of RFI signals might help mitigate this issue by leading to additional and better focused RFI detection algorithms and it might help identify RFI emitters on the ground. In this study we present approaches to retrieve some of the features of the RFI signals using SMAP data and we present some statistical considerations about the temporal and spectral characteristics of RFI sources.

We present a physics-based algorithm for retrieving sea surface salinity from L-band radiometric observations from the NASA SMAP instrument. The model is used to assess the radiometer calibration and its long-term stability and produce salinity products that are evaluated against in situ measurements from the Argo network of drifting floats.

Radio Frequency Interference (RFI) at 18.7 GHz in and around the continental United States observed by passive microwave radiometers such as the Global Precipitation Measurement (GPM) Microwave Imager (GMI) has been noted in multiple publications. A large part of this RFI arises from reflected geosynchronous direct broadcast satellite transmissions. The interference yields surprisingly high artificial brightness temperature values, ranging from a few Kelvin up to over 1000 Kelvin. Some of the highest levels and most direct reflections occur over land from specular reflections from smooth surfaces such as lakes and rivers. Over the ocean surrounding the United States, the reflections are generally less directional, occurring at higher glint angles and often with lower peak levels than over land. The interference corrupts the GMI measurements about 13% of the time over the ocean around the US, and over 5% of the time over the affected land areas.

Microwave remote sensing relies on the utilisation of the electromagnetic spectrum, which is becoming a precious commodity due to increasing demand by commercial telecommunication and other radio services. The access to this resource is regulated by the International Telecommunication Union, which periodically holds a World Radiocommunication Conference (WRC) where representatives from different countries meet to define international rules for its use.The next WRC will take place in November 2019, and the Frequency Allocations in Remote Sensing (FARS) Technical Committee of the IEEE Geoscience and Remote Sensing Society (GRSS) has prepared a report discussing the Agenda Items of the conference that are most relevant to remote sensing. This contribution will explain the issues at stake for remote sensing at WRC-19, illustrate the document conclusions and provide suggestions on what remote sensing scientists and engineers can do to become more involved in tackling these issues.

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.

As world-wide microwave service technology advances, the associated Radio Frequency Interference (RFI) to passive Earth-observing microwave radiometers also evolves over time. This paper builds upon an RFI detection technique developed for the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and applies it to the Advanced Microwave Scanning Radiometer (AMSR) Earth - Observing System (EOS) (AMSR-E) and its follow-on mission AMSR2. The two AMSR instruments provide a 15+ year time series (starting in 2002) of Earth observations to analyze RFI environment in frequency bands used by radiometers from C-band through W-band. This work focuses on C-, X-, and K-band channels from 2002 to 2015. While it is commonly assumed that the RFI extent is constantly increasing, this paper shows that in some more developed areas of the world, land-based RFI has been decreasing, while increasing in less developed areas. Temporal trends of the most RFI-prone areas of the world are presented.

Aquarius has produced maps of salinity by measuring Earth's natural emissions at L-band. However, measurements made by its instruments are affected by the presence of Radio Frequency Interference (RFI). For this reason, RFI detection algorithms had been implemented, both for the radiometer and the scatterometer, in order to reduce the impact of RFI on science data. In an effort to improve understanding of L-band RFI, the Aquarius mission has generated a new series of products. This contribution presents how these products were produced as well as the information that they contain. These products will be available starting at the end of January 2018 on the Aquarius website.

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

Aquarius is an microwave active/passive sensor whose main goal is to globally estimate sea surface salinity from space [1, 2]. Two instruments, a radar scatterometer and a radiometer, operate at L-band observing the same surface footprint almost simultaneously. The sensitivity to sea surface salinity (SSS) is given by the radiometer, while the scatterometer measurements provide a correction for sea surface roughness. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. Radio Frequency Interference (RFI) can occur in both the radiometer and the scatterometer bands of operation, and for this reason detection and mitigation of RFI was included in the data processing of both active and passive instruments. This paper will focus on the RFI processing for the Aquarius radiometer only and provide an update on the efforts to reduce the amount of missed RFI detection.

Ocean salinity and soil moisture are key parameters for understanding the global water cycle, weather, and climate. These parameters are being measured with spaceborne radiometers operating in the L-band window at 1400-1427 MHz. Although man-made activity in this band is prohibited, radio frequency interference (RFI) is still a problem over significant portions of the earth. This paper reports a comparison of the RFI environment in this window as observed by two L-band radiometer systems, Aquarius and Soil Moisture and Ocean Salinity. The observed RFI environment depends on the sources and also on the characteristics of the instrument. Comparing the observations provides insight into the extent of the problem (actual sources), the influence of the instrument on the observation of RFI, and on potential ways of mitigating the effects. As this report shows, the global distribution of RFI is largely consistent between the two instruments, but the details, especially at low levels of RFI, depend on the characteristics of the instrument.

Aquarius is an L-band active/passive sensor designed to globally map sea surface salinity from space [1, 2]. Two instruments, a radar scatterometer and a radiometer, observe the same surface footprint almost simultaneously. The radiometer is the primary instrument for sensing sea surface salinity (SSS), while the scatterometer is included to provide a correction for sea surface roughness, which is a primary source of error in the salinity retrieval. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. An important feature of the data processing includes detection and mitigation of Radio Frequency Interference (RFI), which is done separately for both active and passive instruments. Correcting for RFI is particularly critical over ocean because of the high accuracy required in the brightness temperature measurements for SSS retrieval. It is also necessary for applications of the Aquarius data over land, where man-made interference is widespread, even though less accuracy is required in this case. This paper will provide an overview of the current status of the Aquarius RFI processing and an update on the ongoing work on the improvement of the RFI detection and mitigation performance.

Active/Passive instrument combinations (i.e., radiometer and radar) are being developed at L-band for remote sensing of sea surface salinity and soil moisture. Aquarius is already in orbit and SMAP is planned for launch in the Fall of 2014. Aquarius has provided for the first time a simultaneous look at the Radio Frequency Interference (RFI) environment from space for both active and passive instruments. The RFI environment for the radiometer observations is now reasonably well known and examples from Aquarius are presented in this manuscript that show that RFI is an important consideration for the scatterometer as well. In particular, extensive areas of the USA, Europe and Asia exhibit strong RFI in both the radiometer band at 1.41 GHz and in the band at 1.26 GHz employed by the Aquarius scatterometer. Furthermore, in areas such as the USA, where RFI at 1.4 GHz is relatively well controlled, RFI in the scatterometer band maybe the limiting consideration for the operation of combination active/passive instruments.

Aquarius is an L-band radiometer system designed to map sea surface salinity from space. This is a sensitive measurement, and protection from radio frequency interference (RFI) is important for success. An initial look at the performance of the Aquarius RFI detection and mitigation algorithm is reported together with examples of the global distribution of RFI at the L-band. To protect against RFI, Aquarius employs rapid sampling (10 ms) and a “glitch” detection algorithm that looks for outliers among the samples. Samples identified as RFI are removed, and the remainder is averaged to produce an RFI-free signal for the salinity retrieval algorithm. The RFI detection algorithm appears to work well over the ocean with modest rates for false alarms (5%) and missed detection. The global distribution of RFI coincides well with population centers and is consistent with observations reported by the Soil Moisture and Ocean Salinity mission.

Aquarius is an L-band instrument designed to map sea surface salinity from space. Monitoring salinity from space is a particularly sensitive measurement and RFI is a concern, even in the protected band at 1.4 GHz where the Aquarius radiometers operate. To protect against RFI, the Aquarius radiometer samples rapidly and a glitch detection algorithm is employed to check each sample for RFI. This strategy has worked well over oceans, but there are large areas over land, especially in Asia and Europe, where contamination by RFI affects most samples.

Spaceborne radiometric measurements at L-band from the Aquarius instrument are compared to numerical model simulation. The empirical calibration of the data, performed over oceans only, is checked for consistency with measurements over the celestial sky. The calibration for the horizontal polarization is found to extend properly to the cold sky temperature, but the vertical polarization exhibit large biases, questioning the calibration accuracy over the whole dynamic range of measurements. The dependence of measurements on wind speed and wind direction is compared to model predictions. The accuracy of the model for surface roughness impact is estimated to be of the order of 0.25K over a large range of wind speeds, but is less accurate at the low and high end of the wind speed range, particularly for wind speeds much larger than 15 m/s. The impact of wind direction, while measureable at large wind speeds, is more uncertain to quantify because its amplitude is close to that of the radiometric noise.

Performance of the Radio Frequency Interference (RFI) detection and mitigation algorithms used by the Aquarius microwave radiometer is demonstrated on orbit. The detection algorithm makes use of the radiometer's high over-sampling rate to identify short, pulsed increases in power that are characteristic of radar operating nearby in the microwave spectrum. The over-sampled data are downlinked to the ground, which allows the detection algorithm to be implemented in ground processing. Access to over-sampled data on the ground also enables the mitigation algorithm, which removes samples with detected RFI from subsequent averaging. The mitigation algorithm is shown to remove nearly all detected RFI. The algorithm can also be used to characterize the RFI itself - in particular the probability distribution of its strength and its geolocation. A first look at both characteristics of the RFI are also presented here. As expected, the prevalence and strength of the RFI is found to be much greater over land than ocean. Certain regions of the globe -e.g. in and around Western Europe and Eastern and Southern Asia- have stronger and more frequent RFI.

A numerical simulator has been developed to study remote sensing from space in the spectral window at 1.413 GHz (L-band), and it has been used to optimize the cold-sky calibration (CSC) for the Aquarius radiometers. The celestial sky is a common cold reference in microwave radiometry. It is currently being used by the Soil Moisture and Ocean Salinity satellite, and it is planned that, after launch, the Aquarius/SAC-D observatory will periodically rotate to view “cold sky” as part of the calibration plan. Although radiation from the celestial sky is stable and relatively well known, it varies with location. In addition, radiation from the Earth below contributes to the measured signal through the antenna back lobes and also varies along the orbit. Both effects must be taken into account for a careful calibration. The numerical simulator has been used with the Aquarius configuration (antennas and orbit) to investigate these issues and determine optimum conditions for performing a CSC. This paper provides an overview of the simulator and the analysis leading to the selection of the optimum locations for a CSC.

The third Stokes parameter will be observed from space for the first time at L-band by the Soil Moisture and Ocean Salinity and Aquarius/SAC-D satellites. The correlation between polarizations, which is the source of the third Stokes parameter, is of interest at L-band to measure Faraday rotation and also to indicate novel features of the surface. However, spurious signals (false indication of correlation) can occur in the third Stokes parameter. For example, this happens when the radiometer crosses boundaries associated with a large change in brightness temperature, such as land-water boundaries. In this paper, calculations with the Aquarius radiometer antennas will be used to show that these spurious signals are due to the cross-polarization coupling and large beamwidth associated with realistic L-band antennas in space.

Spurious spikes in the third Stokes parameter have been observed in numerical simulations of the signal expected from the L-band radiometers to be flown as part of the Aquarius instrument. These signals are present over scenes with large contrast such as land water boundaries and are due to cross polarization coupling and the relatively large footprint of the antennas.

This letter describes the effect of thermal emission from the Moon on remote sensing of sea surface salinity from space. In most cases, radiation from the Moon is negligible; however, at several times during the lunar cycle, it is possible for radiation to be reflected from the Earth's surface into the main beam of the radiometer antennas. The signal in such cases can be important because of the high radiometric accuracy required to monitor salinity. Examples are presented using the Aquarius orbit and antennas for both smooth and rough ocean surfaces.

The Aquarius/SAC-D mission will employ three L band (1.41 GHz) radiometers dedicated to remote sensing of Sea Surface Salinity. The mission will be in a dawn/dusk sun synchronous orbit with the beam oriented toward the night time side of the orbit in order to limit interference from the Sun. The effect of surface roughness on solar radiation reflected from the surface will be examined. It will be shown that including the small scale roughness (waves) can have a major impact. Also, it will be shown that when the small scale waves are included it is possible to have significant radiation reflected into the main beam during seasonal extremes when a portion of the main beam is on the illuminated side of day-night terminator.

The influence of the antenna pattern on measured Faraday rotation is examined in the context of passive remote sensing at L-band. It is shown that while I = Tv + Th is independent of Faraday rotation to first order, I has rotation dependence when realistic antenna patterns are included in the analysis. Also, it is shown that the angle retrieved from the 3rdStokes parameter can be biased relative to Faraday rotation at boresight.

The influence of the pattern of the receive antenna on measured Faraday rotation is examined in the context of passive remote sensing of soil moisture and ocean salinity at L-band. Faraday rotation is an important consideration for radiometers on future missions in space, such as SMOS and Aquarius. Using the radiometer on Aquarius as an example, it is shown that, while I = Tv + Th is independent of Faraday rotation to first order, it has rotation dependence when realistic antenna patterns are included in the analysis. In addition, it is shown that using the third Stokes parameter to measure the rotation angle can yield a result that is biased by as much as 1deg by purely geometrical issues that are associated with the finite width of the main beam.