Search

CN006 is the name given by the European Space Agency (ESA) in their reports on radio frequency interference (RFI) to an instance of RFI in the L-band spectral window at 1.413 GHz protected for passive use only. The source of the interference is located east of the Chinese city of Hangzhou in an area with radar installations. Its effect was initially indistinguishable from that of many such RFI sources observed by the ESA's SMOS and NASA's Soil Moisture Active Passive (SMAP) radiometers over China. However, in July 2020, the level of radiation increased dramatically reaching levels exceeding 1700000 K as reported by Soil Moisture and Ocean Salinity (SMOS) becoming the strongest source observed by SMOS. This article describes an analysis of this very strong source (a radar). It provides information to provide insight into an example of a well-defined source of RFI and illustrates the powerful capability of the SMAP radiometer receiver and RFI processing incorporated in it for identifying and understanding interference.

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.

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.

Radio frequency interference (RFI) is a well-documented problem for passive remote sensing of the Earth at L-band even though the measurements are made in the protected band at 1.413 GHz. Consequently, filtering for RFI is an important early step in the processing of measurements made by the SMAP (Soil Moisture Active/Passive) radiometer. However, the filtered data still include regions with suspiciously high antenna temperatures. One possible cause of these “hot spots” is interference not fully detected during RFI filtering. This paper presents evidence supporting this hypothesis and describes an algorithm to identify these “hot spots” so that they can be removed from the measurements. The impact of removing these “hot spots” is generally small, but evidence is presented that the brightness temperature and soil moisture improve when the hot spots are removed.

Fair and efficient management of the radio-frequency (RF) spectrum as used by different scientific and commercial services is becoming more and more challenging, and this can have a considerable impact on microwave remote sensing. Here, we provide an overview of those spectrum management aspects relevant to the remote-sensing community, along with an introduction to the actors and processes involved in spectrum regulation, including the World Radiocommunication Conference (WRC).

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.

Radio Frequency Interference (RFI) is a well-documented problem for passive remote sensing of the Earth at L-band even though the measurements are made in the protected band centered at 1.413 GHz. Consequently, filtering for RFI is an important early step in the processing of measurements made by the SMAP (Soil Moisture Active/Passive) radiometer. However, the filtered data still include regions with suspiciously high antenna temperatures. One possible cause of these “hot spots” is interference not fully detected during RFI filtering. This paper presents some evidence supporting this hypothesis and describes an algorithm to identify these “hot spots” so that they can be removed from the measurements. The impact of removing these “hot spots” is generally small, but evidence is presented that the brightness temperature and soil moisture improve when the hot spots are removed.

The 18.6–18.8 GHz band is utilized extensively for scientific uses. Passive microwave measurements in this frequency range are critical for weather forecasting and studies of climate and environmental impacts. This band, however, is shared with commercial communication systems that operate under the Fixed Satellite Service (FSS). FSS communication is used mostly for satellite TV broadcasting, and by a small number of Very Small Aperture Terminal (VSAT) systems. The Radio Regulations of the International Telecommunication Union (ITU) limit the level of FSS transmitted powers in order to avoid interference to passive sensors that operate under the Earth Exploration Satellite Service (EESS). However, Radio Frequency Interference (RFI) affecting spaceborne microwave radiometers such as WindSat, AMSR2 and GPM-GMI at 18 GHZ has been observed and documented for several years since 2010. Calculations considering sea surface reflection show that the observed RFI is consistent with or higher than what could be expected even from the limited level of transmitted power from the FSS. The IEEE Geoscience and Remote Sensing Society (GRSS) has brought this problem to the attention of the ITU Radiocommunication Sector (ITU-R) Study Groups, in view of impending decisions that could potentially dramatically increase the use of this band by commercial operators. The contributions by IEEE GRSS to ITU-R will be presented and various issues involved will be discussed.

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 Aquarius/SAC-D mission operated between August 2011 and June 2015 with the main goal of providing global estimates of sea surface salinity (SSS). It comprised both active and passive microwave sensors operating at L-band to observe the same surface area almost simultaneously. Measurements from both instruments underwent subsequent filtering to mitigate the effect of Radio Frequency Interference (RFI). However, RFI cannot always be detected, especially when the level of interfering signals is comparable to that of the natural surface emission. A study was performed here to assess the amount of missed detection in certain ocean region where low-level interference is a problem. The approach is to estimate the statistics of RFI starting from the acquired antenna temperature samples. The statistics are then used to simulate RFI and study its detection by the RFI filter. The results of this simulation are compared with the RFI actually detected in the acquired samples to provide an estimate of the level of missed detection.

RFI (Radio-Frequency Interference) in the 1400–1427 MHz band degrades the quality of measurements made by satellite missions such as SMAP (Soil Moisture Active/Passive), Aquarius and SMOS (Soil Moisture and Ocean Salinity). A technique is presented here to estimate the location on the ground of RFI sources using SMAP measurements. The results of this technique have been validated against data derived by other means.

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.

In recent years, three instruments have been launched into orbit with the aim of producing global maps of sea surface salinity and soil moisture using the 1400–1427 MHz band: SMOS, Aquarius and SMAP. Although this frequency band is allocated to passive measurements only, RFI (Radio-Frequency Interference) is present in the data of all three missions. On a global scale, the three sensors have observed approximately the same distribution of RFI. Japan is an important exception that has implications for the design of RFI detection algorithms. RFI in Japan is caused by a large number of emitters belonging to the same system (TV receivers) and for this reason some traditional RFI detection strategies detect little to no RFI over Japan. The study of this case has led to an improvement of the approach to detect RFI in Aquarius data.

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.

Aquarius and SMAP brightness temperature data are used to estimate sea ice thickness in the polar regions. The method is based on the inversion of a radiative transfer model for ice-covered sea. This model predicts the emission from ice-covered sea and is similar to the one used by the SMOS group. The sea ice thickness values retrieved from Aquarius and SMAP measurements using this technique are compared with the SMOS data. Since Aquarius ceased operation due to component failure on at the beginning of June 2015, while the SMAP radiometer began operating at the end of March 2015, data from April 2015 are used in the comparison. Results obtained using Aquarius and SMAP data are consistent with each other, but show a high uncertainty compared to the SMOS sea ice thickness product.