4.7 Article

An Radio Frequency Interference Mitigation Approach for Spaceborne SAR System in Low SINR Condition

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2023.3321087

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Adaptive notch semi-parametric (ANSP) algorithm; interference mitigation; radio frequency interference (RFI); synthetic aperture radar (SAR)

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Synthetic aperture radar (SAR) is an active imaging radar used to obtain high-resolution wide-swath SAR images. However, it is susceptible to radio frequency interference (RFI) from other electromagnetic systems, which can reduce imaging quality. To mitigate RFI, researchers have proposed a novel adaptive method that combines semi-parametric and frequency-domain notched filter methods, effectively dealing with strong RFIs and protecting strong scatterers.
Synthetic aperture radar (SAR) is a kind of active imaging radar, which can obtain high-resolution wide-swath SAR images, especially for spaceborne SAR systems. In practical electromagnetic environment, due to the overlap of same frequency bands, spaceborne SAR is extremely vulnerable to interferences from other electromagnetic systems, called radio frequency interference (RFI) to SAR systems. RFI seriously reduces the imaging quality of the SAR system and causes resolution reduction and scene occluded. To mitigate RFI in SAR systems, researchers have proposed many methods, in which semi-parametric methods, such as robust principal component analysis (RPCA)-based methods, played important roles in strong RFI mitigation in recent years. However, it is observed that they may be hard to recover the true scene well under extremely strong RFIs since the strong scatterers are also mixed in the extracted low-rank interferences. Therefore, in this article, we propose a novel adaptive method, which combines the advantages of both semi-parametric method and frequency-domain notched filter (FNF) method, called adaptive notch semi-parametric (ANSP) method, where the FNF method, as a nonparametric method, can retain more true scenes when mitigating interferences. As a result, the proposed method can not only effectively deal with strong RFIs but also protect the strong scatterers better with an adaptive threshold. This method can recover the true scene under extremely strong RFI and be applied to both Level-0 and Level-1 SAR data. Finally, we conduct experiments on several real SAR data and demonstrate the effectiveness of the proposed method.

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