Pixel-Wise Radio Frequency Interference Mitigation in L-Band Airborne SAR Data

Radio Frequency Interference (RFI) represents one of the major sources of performance degradation for Synthetic Aperture Radar (SAR) systems, especially for those operating at the microwave low-frequencies (e.g., L- and P-bands), where the spectrum sharing with other electromagnetic devices is increasingly common. In this work, pixel-wise RFI detection strategies operating on range-compressed (RC) SAR images are presented and applied to real-world airborne data acquired by the Italian Multiband Interferometric and Polarimetric SAR (MIPS) system. In particular, in the proposed approach, the RFI detection problem is recast in terms of the minimization of a Model Order Selection (MOS) rule, where the number of RFI-corrupted pixels is estimated through information theoretic paradigms, namely the Bayesian Information Criterion (BIC) and the Akaike Information Criterion (AIC). Experimental results demonstrate that the proposed procedure enables the effective suppression of the RFI-induced artifacts observed in the focused images while preserving the useful signal, thus confirming the suitability of the proposed approach for practical applications involving SAR data.