An efficient simultaneous SAR imaging method for multiple moving targets

Synthetic aperture radar (SAR) moving target imaging technology has indisputable benefits in both civilian and military applications, due to the merits of high-resolution and all-weather all-day surveillance. However, it is challenging for imaging multiple moving targets by traditional SAR imaging methods, because of the inevitable variation of Doppler frequency caused by the inconsistent motion of targets. In this paper, we aim at proposing an efficient simultaneous SAR imaging method for multiple moving targets in the framework of sparse recovery. Firstly, we construct the sparse observation model and transform the multiple moving targets imaging problem into two processing stages, i.e., motion phase errors compensation and sparse image recovery. Then the motion phase errors of targets are estimated and compensated via time-frequency representation method, resulting in a sub-echo set. After that, the kernel-based consensus alternating direction method of multipliers (CADMM) which makes full use of the consensus constraint characteristic of sub-echo set, is utilized to efficiently recover the global-focused sparse image. Finally, numerical experimental results demonstrate that the proposed scheme possesses the advantages of noise suppression and simultaneous focusing ability for multiple moving targets.