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

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 non-ideal motion of the airborne platform severely affect synthetic aperture radar (SAR) imaging, particularly in the THz wave band. To address this issue, this paper 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 (RDA) is employed to generate a coarse image and extract the moving target region as the region of interest (ROI). Then the range profile can be obtained by applying the inverse fast Fourier transform (IFFT), which serves as input for the ADMM solving algorithm. Finally, the 2D 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 to conventional algorithms while maintaining high imaging speed without estimating Doppler parameters.