FISTA-based Approach for SAR Image Reconstruction from 1-bit Quantized Data

Abstract

Compressive sensing (CS) provides significant benefits in synthetic aperture radar(SAR) imaging. Recent studies have demonstrated that CS framework is also successful in SAR imaging of sparse scenes with 1-bit quantized measurements. However, available 1-bit CS SAR recovery algorithms have high computational complexity and are much more time-consuming. In this study, we present a solution to 1-bit CS SAR image reconstruction problem. The presented solution technique is based on a fast iterative shrinkage-thresholding algorithm (FISTA) which is popular with computational simplicity and has a significantly better global rate of convergence. The experiments are conducted with synthetically produced SAR data in order to test the effectiveness of proposed FISTA-based approach.