RFI Suppression Based on Linear Prediction in Synthetic Aperture Radar Data
Wei Xu, Weida Xing, Chonghua Fang, Pingping Huang, Weixian Tan
Abstract
Radio frequency interference (RFI) sources pose threats to wideband synthetic aperture radar (SAR) systems and accurate SAR image interpretation. Since most of RFI sources are narrowband, notch filtering is a simple but effective method for RFI suppression. In this letter, a modified two-step notch filtering approach combined with linear prediction is proposed to improve the SAR image quality. The notch filtering is used to mitigate narrowband RFI energy, while the linear prediction is introduced to recover the missing range spectral component of the SAR raw data from the desired scene, which is removed together with RFI sources by the notch filter. Because of the Gibbs phenomenon in Fourier series, the small residual RFI energy after notch filtering is enough to cause image visual disturbances and affect the accuracy of the following missing range spectrum extrapolation. The two-step notch filtering with a limited bandwidth is applied for better RFI sources mitigation. Simulation results on both simulated targets and real SAR raw data validate the proposed approach.