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The existence of radio frequency interference (RFI) has a great influence on the measurement of synthetic aperture interferometric radiometer (SAIR). The strong RFI signal energy picked up by the sidelobes of synthetic beam (or array factor) of SAIR easily results in false positives, deteriorating the RFI detection performance, especially when considering the representative scenes where RFIs have a large dynamic range of intensity. In this paper, we propose a novel RFI source detection method by exploiting the array factor property (AFP) of SAIR. The AFP-based RFI detection (AFPRD) method mainly consists of three steps. First, RFI sources are recovered from visibility function samples through sparse reconstruction (SR). In the recovered RFI map, the background noise is reduced and the potential RFI target regions could be extracted well. Second, the AFP of SAIR is analyzed concerning distribution characteristics of main beam and sidelobes. Based on the AFP analysis, we present a new spatial weight indicator (SWI) describing the probability of one potential RFI being a false positive. Then a SWI-based probability map (SPM) is generated to discriminate true sources with the false positive sources. Third, the SPM and the SR-based map are combined to reconstruct the RFI image, where false positives are filtered out while true RFI sources are retained. The experiments using synthetic data and real SMOS satellite data demonstrate the effectiveness and superiority of the proposed method in RFI detection tasks for SAIR.

A Novel RFI Source Detection Algorithm Using Array Factor Property for Synthetic Aperture Interferometric Radiometer