| The capability of high resolution and wide swath (HRWS) imaging is desired by space based remote sensing and military reconnaissance. But for minimum antenna area constraint, there is an irreconcilable conflict between azimuth resolution and swath in single-channel SAR. This conflict can be mitigated via receiving with multiple channels. With the same resolution, multi-channel SAR can achieve much wider swath than single-channel SAR.Several key problems for multiple-channel SAR imaging are investigated in this paper. Firstly , with regard to single-input and multiple-output (SIMO) SAR, suppression means for range-Doppler ambiguities are studied for the two formation of single platform and distributed satellite SAR respectively because they have different characteristics of distinct baselines among phase centers. Secondly, to multiple-input and multiple-output (MIMO) SAR, problems such as orthogonal waveform design are researched based on studies above for SIMO SAR.Implementation form for SIMO SAR on single platform is comprehensively studied in Chapter 2. Firstly, merit factor for HRWS imaging evaluation is presented according to minimum antenna area constraint. Next, five multi-channel SAR systems are contrastively analyzed on several aspects, such as merit factor, capability for range-Doppler ambiguity suppression, signal to noise rate(SNR), data volume, complexity of signal processing, and blind swath. Conclusively, a reasonable system scheme, with displaced phase centers multiple azimuthal beam (DPC-MAB) and multiple receiving channel in range, is chosen as issue studied below.DPC-MAB SAR with multiple receivers in range is studied in Chapter 3. After building signal model of SIMO SAR, decomposition spectrum algorithm is proposed to ambiguity-free reconstruction for multi-channel SAR echo, by which conventional imaging algorithms can be carried out to achieve HRWS imaging. SNR and azimuth ambiguity signal rate (AASR) of reconstructed data are analyzed and conclusion is drawn that there is conflict among SNR, AASR and PRF. So application of multiple overlapped receiving subapertures with phased array antenna is presented to handle this problem.Distributed satellites SAR for HRWS imaging is studied in Chapter 4. For SAR-Train without cross-track baseline, preprocessing method is proposed for compensation for mutuality losing in echoes from multiple satellites. Then, the SAR-Train formation can be transformed to DPC-MAB and method given in Chapter 3 can be implemented in this formation. For the formation as"TanDEM-X", an idea is presented to transform echoes from bistatic SAR multiple channels into echo from bistatic SAR with single channel equally. As regard to distributed SAR system with cross-track baseline, Phase history difference of two receiving channels is approximated by the second taylor expansion and compensated respectively. Range-dependent characteristic for phase histroy difference is analyzed and frequency compensation method is presented.MIMO-SAR is researched to improve performance of HRWS imaging in Chapter 5. Based on theory analysis and simulation, an impartant conclusion is drawn that phase-coded waveforms and Costas waveforms will fail to fulfill land mapping MIMO-SAR for the constraint between autocorrelation function and cross-correlation function. Stepped frequency LFM signal is proved to have ideal orthogonal performance and can be adapted to MIMO-SAR. Signal processing method for this kind of waveform and simulation results are presented. To break up the limitation of failing to jointly processing in azimuth dimension with different frequency band stepped frequency LFM signals, space-time orthogonal waveform is proposed to achieve more equivalent phase centers and better HRWS imaging performance. Besides these advantages, space-time waveform can avoid interference dark speckle on the ground scene brought by transmitting signals simultaneously at the same frequency. Performance for range-Doppler ambiguity suppression is analyzed and signal processing method is also researched.
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