Research On Ground Moving Target Detection Technology In Multichannel SAR System

Ground moving target indication(GMTI) based on the airborne or spaceborne synthetic aperture radar(SAR) system is a hot topic in the area of SAR in recent years. It has an important significance in both military and civil applications. Due to the poor detection performance of the single-channel SAR system, GMTI for multichannel SAR has great research potential and broad development prospects. Therefore, GMTI based on the airborne or spaceborne multichannel SAR system is researched deeply in this dissertation. The geometry model of multichannel SAR system and the echo model of SAR moving target is constructed, then the moving target detection algorithms based on the Displaced Phase Center Antenna(DPCA) clutter suppression technique, the Space-Time Adaptive Processing(STAP) clutter suppression and Compressive Sensing(CS) theory are researched in this dissertation, the aims to improve the detection performance of moving target, especially the slow moving target, and solve the problem of large amount of raw data in multi-channel SAR system. The primary works of the dissertation include:(1) The geometry model of multichannel SAR system and the echo model of SAR moving target are constructed based on the multichannel SAR-GMTI system. The influence of motion parameters on SAR imaging is analyzed from the theoretical deduction and simulated experiments. Moreover, the key of the moving target indication is to clutter suppression effectively by analyzing the frequency spectrum and statistics of the ground clutter;(2) The moving target detection algorithm based on DPCA is studied in the dual-channel SAR-GMTI system. The DPCA methods in the time domain, in the Doppler frequency domain and in the image domain are analyzed from the theoretical deduction and simulated experiments to validate the feasibility and effectiveness of the algorithm. Furthermore, the minimum detectable velocity, the maximum detectable velocity, the blind velocity and channel unequalization on the DPCA algorithm are discussed. In addition, the detection performance of the algorithm in the homogeneous environment and heterogeneous environment is analyzed in this dissertation;(3) The moving target detection algorithm based on STAP is researched in the multichannel SAR-GMTI system. The STAP methods in the time domain, in the Doppler frequency domain and in the image domain are analyzed from the theoretical deduction and simulated experiments to validate the feasibility and effectiveness of the algorithm. In addition, the detection performance and improvement factor of the algorithm in the homogeneous environment and heterogeneous environment are analyzed in this dissertation to prove the superiority of the algorithm. The detection performance of the slow moving target and the target with low SCNR is superior to that of the DPCA algorithm. With the advantages of the long baseline and short baseline, the moving target detection method based on the STAP in the image domain with the non-uniform array is proposed that achieves the less minimum detectable velocity and expands the maximum unambiguous range of the radial velocity at the same time. Moreover, the STAP algorithm in the image domain based on the multi-pixel processing is proposed in order to improve the detection performance and the adaptability of the registration error further;(4) The enormous amount of sampling raw data from the multichannel SAR system makes difficulties in storage and transmission. Therefore, the moving target detection algorithm based on CS theory is researched in this dissertation. The echo model with sparse sampling of the multichannel SAR system and the measurement matrix are constructed due to the ground moving target is sparse in spatial domain. In addition, three reconstruction algorithms are introduced. Based on the Bayesian Compressive Sensing(BCS), the DPCA-BCS algorithm in dual-channel SAR-GMTI system and STAP-BCS algorithm in multichannel SAR-GMTI system are proposed in this dissertation. The feasibility and effectiveness of the algorithms are validated via the theoretical deduction and simulated experiments. It achieves the detection of moving target with sparse sampling. Moreover, the detection performance of different reconstruction algorithms and sparse sampling models is analyzed and compared. According to meet the DPCA condition for STAP-BCS algorithm, the improved algorithm is proposed to make the SAR-GMTI system more flexible and the better detection performance of the moving targets.