The Aquarius Radiometers and Radio Frequency Interference: Analysis of RFI at L-band and its Impact on Salinity Retrieval
Contact author: Paolo de Matthaeis, <email@example.com> All Authors:
Paolo de Matthaeis, GESTAR, NASA Goddard Space Flight Center, Greenbelt, MD
Seung-bum Kim, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA
Yan Soldo, GESTAR, NASA Goddard Space Flight Center, Greenbelt, MD
David Le Vine, NASA Goddard Space Flight Center, Greenbelt, MD
Aquarius is a combined L-band radiometer/scatterometer system designed to map sea surface salinity from space. The salinity retrieval is based on the relationship with brightness temperature, that therefore need to be measured with great accuracy. Although the three Aquarius radiometers operate in the frequency range from 1400 to 1427 MHz that is allocated to passive remote sensing services and radioastronomy, unwanted interference can still be present, both from illegal sources and due to spillover emissions from nearby bands. For this reason, great efforts were made during instrument design to include detection and mitigation of Radio Frequency Interference (RFI) in the Aquarius data processing. As a result, Aquarius has been able to successfully identify RFI and reduce its impact. However, while the most obvious interference has been taken care of, much work remains to be done in order to handle more subtle problems due to undetected RFI and false RFI detection. In this work, some observed changes in regional RFI environments are analyzed with the goal of better understanding the performance of the Aquarius RFI algorithm in particular situations such as when low-level or non-impulsive interference is present. The effect and implications on the salinity retrieval are presented and discussed.
Rising Above the Noise: Estimating and Removing Low-Level Undetected RFI Contamination in the Aquarius Salinity Product
Contact author: Shannon Brown, <firstname.lastname@example.org>
Shannon Brown, Jet Propulsion Laboratory
Radio Frequency Interference (RFI) is a well documented issue for microwave radiometry, and L-band radiometer in particular. To mitigate against RFI, the Aquarius radiometer processing using a time-based filter, where observations that are greater than about 4-sigma above the noise floor are tagged as being RFI and removed. This filter is applied to the 10ms Aquarius observations prior to averaging to the baseline 1.44 second sampling. This algorithm works well for strong RFI sources, but is blind to any low-level RFI that is below the 4-sigma level above the noise. This case occurs frequently over the ocean within about 1000km of land, where RFI enters from many directions through the antenna pattern sidelobes. The antenna pattern reduces the magnitude of interference by typically 30dB, but when the sources combine, it is not uncommon for these sources to bias the radiometer TBs by 0.5 K, which would not be detectable with the RFI mitigation algorithm. This paper describes an algorithm to remove this low-level RFI which can be applied to future Aquarius processing versions. The algorithm uses pre-computed ascending and descending RFI contamination maps to remove the bias due to this contamination. This presentation will focus on how the RFI maps are generated. The first part is identifying the location of the sources and the second part is identifying their strength. This is done iteratively by minimizing a cost function between the observed ascending-descending TB differences for each horn and a forward model of the Aquarius antenna patterns convolved with the pre-identified RFI source locations. The presentation will provide an estimate for the algorithm performance and residual errors.