Paolo de Matthaeis

Aquarius RFI Detection and Mitigation Algorithm: Assessment and Examples

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.

Passive Remote Sensing and Radio Frequency Interference (RFI): An Overview of Spectrum Allocations and RFI Management Algorithms [Technical Committees]

The Frequency Allocations in Remote Sensing (FARS) Technical Committee (TC) was formed in 2000 as a means for the IEEE Geoscience and Remote Sensing Society (GRSS) community to discuss spectrum management issues that affect the remote sensing field and to provide a unified interface to the regulatory world. Presently, FARS members include 84 engineers and scientists representing government, academic and industrial entities across 10 countries.

Aquarius radiometer RFI detection, mitigation and impact assessment

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 radiometers 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.

Sea surface salinity variability in the East China Sea observed by the Aquarius instrument

This study demonstrates that the spaceborne Aquarius instrument is able to monitor the sea surface salinity (SSS) variations in the East China Sea (ECS) with the spatial resolution of about 150 km at 7 day interval, where routine observations are difficult. The two geophysical contaminants enter the sidelobes of the Aquarius antenna and bias the coastal SSS low: the emission from the land surface and the radiofrequency interference (RFI). Away from about one Aquarius pixel (150 km) from the coastline, the Aquarius SSS is fairly insensitive (less than about 0.2 psu) to the radiometric details of the method to correct for the land emission. The ascending orbits appear to be affected by unfiltered RFI much less than the descending tracks. The Aquarius SSS along the ascending tracks is low over the ECS by 0.40–0.93 psu (with respect to the in situ data during the two separate 7 day periods) and is biased low by 0.41–1.07 psu (accuracy, or the time-mean of difference from the regional model along three Aquarius tracks over a 18 month period). The presence of the ascending and descending differences in the Aquarius SSS, and the spatially widespread bias suggest that the bias is attributed to the unfiltered RFI originating from strong point sources (rather than to the land contamination from weak distributed sources, or to other seasonally varying geophysical contaminants). Despite the bias, the Aquarius data describe well the temporal and spatial variability of the ECS SSS. The temporal trend and magnitude of salinity changes agree remarkably between Aquarius and a regional numerical model, during both the freshwater discharge season from the Yangtze river and the rest of the year. The precision of the Aquarius observation in the ECS is comparable with the Aquarius mission requirement (0.2 psu one-sigma for a monthly average over the open ocean). The river discharge rate correlates with the Aquarius SSS with the coefficient of 0.71 on a seasonal scale with the discharge leading the SSS changes. The Aquarius SSS increases away from the coast, in response to the river outflow. The interannual changes in the Aquarius SSS capture the effect of the regional drought in summer 2013.

L-Band RFI Detected by SMOS and Aquarius

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.

L-band RFI in Japan

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.

Analysis of RFI statistics for Aquarius RFI detection and mitigation improvements

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.

Sea ice thickness retrieval at L-band: Comparison between results from Aquarius and SMAP data

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.

RFI detection and mitigation for Aquarius: Status and ongoing improvements

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.