在星载合成孔径雷达(SAR)平台向轻小型化发展的进程中，间断调频连续波(IFMCW)体制SAR因其具有轻重量、小体积、低功耗、低数据率的优势，是一种经济实用的体制方案。在IFMCW SAR成像上，发射模式和接收模式的交替会在合成孔径的过程中形成数据间断，这些间断将会在目标两侧引入伪峰。针对此问题，提出基于压缩感知的IFMCW SAR方位向间断数据重构方法，首次将分段正交匹配追踪(StOMP)和稀疏度自适应匹配追踪(SAMP)数据重构算法运用在IFMCW方位数据重构中，解决了现有算法依赖场景稀疏度先验知识的问题。同时优化了SAMP算法结构，提升算法对IFMCW SAR数据重构的适用性。通过对IFMCW SAR仿真点目标回波数据和地面真实场景回波数据处理，验证所提2种算法在无场景稀疏度情况下的有效性。最后在处理速度和重建效果方面将StOMP和改进SAMP与原算法进行对比，体现了不同处理场景下改进SAMP算法对稀疏场景处理的良好性能和StOMP对复杂场景的处理优势。
The interrupted frequency modulated continuous wave (IFMCW) SAR is an economical and practical solution for the development of light-duty and miniature spaceborne synthetic aperture radar (SAR) systems due to its light weight, small size, low power consumption, and low data rate. However, data interruptions occur in the received azimuthal signals due to the alternation between the “transmit” and “receive” modes of IFMCW SAR, which lead to pseudo-peaks on both sides of the target in the imaging result. In this paper, a compression sensing-based azimuthal interrupted data reconstruction method for IFMCW SAR is proposed, employing stage-wise orthogonal matching pursuit (StOMP) and sparsity adaptive matching pursuit (SAMP) to azimuthal data reconstruction for the first time. The proposed method solves the problem of the existing algorithm, which requires sparsity as a priori knowledge. In addition, the method optimizes the SAMP structure, which improves the applicability of the algorithm on IFMCW SAR’s data reconstruction. The effectiveness of the proposed algorithms is verified by processing both simulated point target and ground truth echo data with unknown sparsity. Furthermore, the processing speed and reconstruction effect are compared with the original algorithm, revealing the good performance of the improved SAMP algorithm in sparse scenarios and the advantage of StOMP in complex scenarios.
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