An Equalized ADMM-Based High-Resolution Autofocusing Imaging Algorithm for THz-SAR Ground Moving Targets

Abstract

Terahertz (THz) radar is well-suited for dynamic mobile target surveillance due to its high frame rates, minimal delay, and superior resolution. However, the defocusing problem caused by the motion of targets in the scene and the nonideal motion of the airborne platform severely affect synthetic aperture radar (SAR) imaging, particularly in the THz wave band. To address this issue, this article proposes a high-resolution imaging algorithm for THz-SAR ground-moving targets using the equalized alternating direction method of multipliers (ADMM). First, the range-Doppler algorithm is employed to generate a coarse image and extract the moving target region as the region of interest. Then, the range profile can be obtained by applying the inverse, which serves as input for the ADMM solving algorithm. Finally, the 2-D image of the target is reconstructed iteratively. The algorithm fully exploits the low-rank and sparse characteristics of moving targets in the SAR image to separate them from the background. It updates the azimuthal matched filter iteratively by minimizing image entropy and designs the equalization factor to retain target details while maintaining image sparsity. This approach significantly improves focusing accuracy compared with conventional algorithms while maintaining high imaging speed without estimating Doppler parameters.

Keywords

• Alternating direction method of multipliers (ADMM)
• moving target imaging
• regularization optimization
• synthetic aperture radar (SAR)
• terahertz (THz)