一种高分辨的稀疏孔径ISAR成像方法

逆合成孔径雷达回波缺失程度较大时，传统的线性插值方法会带来较大的误差．针对这一情况，提出了一种基于压缩感知的稀疏孔径高分辨成像算法．通过构造一组时域稀疏的基空间和线性测量矩阵，结合范数1稀疏约束，利用凸优化进行基匹配搜索，直接提取目标的散射特性及多普勒频率信息，最终得到距离多普勒像．该方法无需对稀疏孔径进行插值，并且成像结果不存在旁瓣，对目标分辨特性较好．点目标模型仿真和实测数据处理的结果验证了该算法的有效性和优越性．

High resolution imaging method for the sparse aperture of ISAR

The conventional linear interpolation method will introduce the estimation error when the gapped data of ISAR is large. A high resolution imaging method based on compressed sensing for gapped data of ISAR is proposed in this paper. We first construct a sparse basis dictionary and linear measurement matrix. Then the convex optimization means as the base pursuit can be used to extract the scatter property and Doppler frequency information. By all the steps above, the image of ISAR is formed in the plane of range and Doppler. No interpolation is needed for the sparse aperture, and no sidelobes exit in the ISAR images. Simulation results and real sparse ISAR data validate the feasibility and superiority of the approach.