Wide Angle SAR Subaperture Imaging Based on Modified Compressive Sensing

Abstract

In wide angle synthetic aperture radar (WASAR), the scattering behavior varies with aspect angle. Subaperture methods can be adopted to accommodate the anisotropic behavior. Modified compressive sensing (MCS) focuses on reconstructing a sparse signal from a limited number of its linear projections when a part of its support is known. It can achieve the accurate recovery with less samples compared with the traditional compressive sensing (CS). Since the support sets of different subaperture images are highly overlapped across the whole aperture, MCS can be adopted in WASAR subaperture imaging. Iterative hard thresholding with partial known support (IHT-PKS) is adopted to recover the MCS model. Azimuth-range decouple operators based on backprojection are implemented in IHT-PKS to avoid huge memory cost of the measurement matrix. Compared with the traditional CS-based WASAR subaperture imaging method, the proposed method can reconstruct the aspect dependent scattering more accurately and is more robust to noise. The proposed method can also reconstruct the scene with less undesirable artifacts at downsampling rate. The simulation and experiment results validate the proposed method.