Research on Anti-interference Performance of Sparsity-based SAR Imaging

Abstract

Sparsity-based radar imaging has attracted much attention in recent years because of its potential advantages in improving image quality (via regularization) and reducing sampling rate (via compressed sensing). Since the matched filtering that provides a large process gain is replaced by non-linear optimization, it is quite necessary to investigate the robustness of this microwave imaging mechanism under the condition of disturbance from a new perspective. In this paper, we focus on the research of anti-interference performance of sparse synthetic aperture radar (SAR) imaging under incoherent interference which is divided into sparse and non-sparse models according to the coefficient distribution on Fourier basis. Given that the process of SAR imaging can be considered as an optimal estimation problem, we establish the sparse recovery model for SAR and then analyze the impact of sparsity and coherence measure on separation recovery for sparse case, and interference projection for non-sparse case. Besides, we also carry out simulations to verify the results of analysis which provide basic support and guidance for the design of interference suppression method in the future.