A Moving Target Detection Method for Airborne Multichannel Circular SAR Based on Post-Doppler STAP

As a new observation mode, circular synthetic aperture radar (CSAR) overcomes the limitation of traditional linear SAR. It can observe the fixed area for a long time and achieve moving target tracking. In 2021, The Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS) carried out the airborne digital array SAR experiment. In this paper, the system is briefly introduced and the sub-aperture post-Doppler space-time adaptive processing (PD-STAP) is adopted to process the data. The training data play an important role in the applications of the PD-STAP. Herein, the generalized inner product (GIP) test is utilized in the space-Doppler domain to eliminate the inappropriate training data. Moreover, considering the partially homogeneous environment, a segmented estimation method of clutter covariance matrix (CCM) along the range direction is proposed, which improves the accuracy of the CCM, and a multi-thread PD-STAP implementation based on Graphics Processing Unit (GPU) parallelization is designed. These have improved the performance of PD-STAP in the real applications. Experimental results show that the method can increase the signal-to-clutter plus noise ratio (SCNR) by about 10 dB and achieve 20x speedup for target detection.