基于压缩感知的ISAR高分辨成像算法

针对 ISAR 在短孔径条件下存在的方位向分辨率低、易受噪声干扰等问题，基于压缩感知理论，提出了一种适用于短孔径时间模式下的基于压缩感知的ISAR方位向高分辨成像算法--PH-SL0算法。该算法首先构建部分随机化哈达玛矩阵作为量测矩阵，PH 矩阵具有重构精度高、重构需要量测个数少的优点；然后将运算速度快、重构精度高且稳健性好的平滑0-范数法（SL0, smoothed L0-norm）推广应用到雷达复数域进行信号重构，实现 ISAR的横向高分辨成像；最后对在短 CPI条件下提出的 PH-SL0算法的横向分辨率问题进行了理论分析。仿真和实测数据结果表明，所提算法具有更高的聚焦性能、分辨率以及较好的抗噪性能。

High resolution ISAR imaging algorithm based on compressive sensing

According to the problem that conventional imaging algorithms have some unavoidable shortcomings such as low resolution of image and being fragile to the noise with short coherent processing interval (CPI), an improved ISAR imaging algorithm via CS method, namely, PH-SL0 algorithm, was proposed. In the proposed algorithm, as a kind of measure matrix, partial randomizer Hadamard matrix (PH) has many advantages such as high reconstruction precision and low dimension of measure matrix. Meanwhile, as a reconstruction algorithm, SL0 has many advantages such as demanding fewer measurements than existing methods, having higher reconstructed accuracy and better robust. Therefore, making use of the advantages of PH and SL0, and extending them to the field of radar, the azimuth imaging with short imaging data could be implemented. Finally, simulation results and experimental results of real data show that the algorithm has higher imaging resolution and better robust to noise.