The Study Of Ground Moving Target Detection And Imaging For Airborne Dual-Channel SAR

The dissertation focuses on the study of airborne dual-channel SAR/DPCA system, including DPCA clutter suppression algorithms, error analysis, channel equalization and moving target indication and imaging. On the other hand, multi-channel SAR/SATP clutter suppression technique is introduced and discussed considering the shortcoming of SAR/DPCA system. The primary works of the dissertation include:1. The dissertation introduces simply SAR imaging theory, the radar equation and the target radar cross section. Based on the model of the echoes backscattered from a pointlike moving object, the dissertation discusses the Doppler performance and SAR image's feature of moving target and the range of azimuth pre-filter ratio of moving target SAR image is confined in theory.2. The dissertation deduces the model of the echoes backscattered from a pointlike moving object and received by a moving dual-channel SAR antenna. In addition, the DPCA algorithms in temporal domain and Doppler frequency domain of raw data are studied and the algorithm in range-Doppler raw data domain comes into more excellence through the comparison of the DPCA algorithms in raw data domain and image data domain.3. Based on the Improvement Factor (IF), the dissertation puts forward a performance analysis model of airborne dual-channel SAR/DPCA system, introduces simply CFAR processing, DPCA condition, blind velocity and Minimum Detectable Velocity (MDV).4. The dissertation puts forward the error analysis model based on the DPCA algorithm in range-Doppler raw data domain, studies the influences in the case of some errors including baseline length error, the velocity error of antenna phase center, antenna pattern mismatch and channel mismatch and draws a conclusion: the performances of moving compensation and channel equalization are crucially influenced the performance of SAR/DPCA system.5. Aiming at the shortcoming of the channel adaptive equalization, a channel blind equalization algorithm for dual-channel SAR/GMTI based on digital signal processing is put forward in the dissertation. The algorithm can estimate the mean values of the amplitude and phase errors and compensate it. It is advantageous that the algorithm is implemented easily and cheaply between SAR/GMTI and antenna system. Another advantage is that the blind equalizer doesn't require training signal during the running operation.6. Based on the actual parameters, the dissertation analyses IF and blind velocity of dual-channel SAR/DPCA system and deduces the range of detectable velocity and MDV.7. The dissertation analyzes range cell migration of moving target based on the 2-D range-Doppler signal model in raw data domain, which is deduced in detail in the dissertation. In the case of no knowledge about range velocity and Doppler frequency rate of moving target, its range walk trajectory can be estimated and compensated by the way of spectral analysis technique.8. The dissertation puts forward the technique system of moving target parameters estimation and imaging in detail. First of all, the range position, the range velocity, Doppler centroid and Doppler frequency rate are estimated by the range walk trajectory of moving target image. Second, after the moving target images pass through the matched filter bank, the azimuth velocity and Doppler frequency rate can be estimated. At last, the moving target can be focused and imaged and its azimuth position can be estimated by utilizing the Doppler parameters on the image after range walk compensation.9. The space-time and space-frequency signal model of SAR/STAP is obtained on the basis of the signal model of dual-channel SAR/DPCA. On the basis of the signal model, the SAR/STAP clutter suppression technique is introduced and studied in the dissertation. It includes the optimal detection theory, the disturbance CSM adaptive estimation algorithm, the disturbance eigenspace analysis, Eigenspace Projection(ESP),DOA vectors estimation and the single Doppler channel Space-Frequency Adaptive clutter suppression algorithm offered by Ender J.G.H..