A SAR Multiple RFI Suppression Method via Frobenius Norm and Iterative Matrix Decomposition

The scarcity and sharing nature of the electromagnetic spectrum present a significant challenge to the stable operation of synthetic aperture radar (SAR) systems, as they are susceptible to interference from other devices operating in the same frequency band, known as radio-frequency interference (RFI). In this article, we propose an effective semiparametric method for suppressing multiple RFI, named the iterative matrix decomposition algorithm based on the Frobenius norm (FIMD), we employ CUR decomposition and a soft-threshold algorithm to update low-rank and sparse matrices within an alternate projection framework. It is observed that there exist distinct distribution characteristics between interference points and strong scattering points in the echo domain. We propose a novel and effective signal protection method, which effectively mitigates the risk of strong scattering points being misidentified as interference signals and subsequently eliminated. In addition, we utilize random singular value decomposition instead of traditional singular value decomposition to enhance convergence speed of. Simulation results demonstrate that our proposed method exhibits superior suppression capability and robustness under varying-to-interference ratio conditions and it can be applied to L0-raw products and L1-SLC products.