MIMO-SAR系统在高分辨率宽测绘带成像、运动目标检测等方面具有巨大的优势，是当前SAR领域研究的热点。但常规阵列MIMO-SAR存在天线阵列质量大、成本高、功耗大、数据量大和下传困难等缺点，这使得单星SAR系统较难采用MIMO体制。稀疏阵列MIMO-SAR由于阵列的稀疏排布，能在保持和提升常规阵列MIMO-SAR成像和检测性能的基础上，具有克服其缺点的潜力。本课题面向稀疏阵列MIMO-SAR的实际应用，在阵列稀疏排布的基础上，结合压缩感知理论，研究稀疏阵列MIMO-SAR高分辨宽测绘带解模糊及成像算法；围绕信号稀疏恢复性能，展开对阵列的优化排布设计；在研究稀疏阵列MIMO-SAR解模糊成像的基础上，提出一种可同时进行动目标检测成像与对静止目标实现高分辨宽测绘带成像的算法。课题的研究对稀疏阵列MIMO-SAR的理论研究和工程实现具有重要意义。

The Multiple-Input and Multiple-Out Synthetic Aperture Radar (MIMO-SAR), with promising prospect in high-resolution and wide-swath imaging, Ground Moving Target Indication (GMTI), is intensively studied in the SAR community. However, the normal array MIMO-SAR suffers from the bottlenecks of overload antenna array, high cost, high power consumption, huge data volume and the hard data transmission, and so on. And they result in the intractability of using normal array MIMO-SAR for space-borne system. Taking advantage of the spars array arrangement, the sparse array MIMO-SAR can potentially overcomes these disadvantages meanwhile not sacrifice the performance of normal array MIMO-SAR. Towards the practical application of sparse array MIMO-SAR and with the Compressive Sensing (CS), this project exploits the removing ambiguity and imaging for MIMO-SAR and the optimized design of sparse array arrangement for recovering signal performance. Based on these issues, a novel algorithm, tackling the GMTI and high-resolution and wide-swath imaging for static state scene simultaneously will be proposed. It is believe that the project is of significance to both the theory research and the engineering implementation for the sparse array MIMO-SAR.