A Moving Target Imaging Algorithm Based on Compressive Sensing for Multi-channel in Azimuth HRWS SAR System

For high-resolution wide-swath (HRWS) multichannel synthetic aperture radar (MC-SAR) system, this paper proposes a novel imaging mode for the ocean moving target. Based on the sparsity of the ocean target images, the new mode uses compressive sensing (CS) to reduce the amount of data by sampling below the Nyquist sampling rate and increases the swath width. Due to the existence of channel error when using the space-time equivalent sampling technique for azimuth signal reconstruction, the traditional single-channel or dual-channel CS-based method is no longer applicable for MC-SAR. In this paper, the moving target imaging is transformed into the sparse signal reconstruction problem under a certain dictionary which constructed based on phase errors called FD-PM (frequency-dependence phase mismatch, FD-PM). The proposed method eliminates the azimuth defocus and blur caused by channel errors and we can obtain images with higher azimuth resolution by a lower sampling rate. Meanwhile, the amount of data is greatly reduced and the imaging efficiency is improved. Simulation data demonstrates the effectiveness of the proposed method.