基于随机调频步进信号的高分辨ISAR成像方法

为充分利用随机调频步进逆合成孔径雷达回波所具有的联合稀疏特征，提高成像性能，该文提出一种基于分布式压缩感知理论的随机调频步进逆合成孔径雷达高分辨成像方法。首先构建随机调频步进信号回波的联合稀疏表示模型，并完成子脉冲的脉冲压缩处理；其次，基于每组子脉冲的随机方式(组与组之间的随机方式不同)，构建相应的随机量测矩阵，获取回波的压缩感知信号模型，并利用分布式压缩感知理论实现距离向联合高分辨重构；最后结合回波在方位向的稀疏性，采用快速稀疏重构算法实现方位向高分辨成像。理论分析和仿真结果表明由于充分利用了随机调频步进信号回波的随机性与联合稀疏特征，所提出方法具有重构精度高、距离向采样率低、抗噪性能强等特点。

High Resolution ISAR Imaging Method Based on Random Chirp Frequency-stepped Signal

In order to make full use of the joint sparse physical characteristics of the radar echo to improve imaging performance. A novel super resolution Inverse SAR (ISAR) imaging method based on distributed compressed sensing theory is proposed. Firstly, the joint sparse echo model of the random chirp frequency-stepped signal is built and the pulse compression processing of each sub-pulse is processed. Secondly, owing to different random patterns of each group, different measurement matrices are constructed in accordance with the random pattern of sub-pulse signal. Then the corresponding compressed sensing model of the echo is built and the supper resolution range profile is obtained via the distributed compressed sensing theory. Finally, the supper resolution inverse synthetic aperture radar image can be obtained by a fast compressed sensing reconstruction algorithm, which is used to achieve the high resolution reconstruction in azimuth direction based on the sparse features. Theoretical analysis and simulation results show that the proposed method has the characteristics of high reconstruction accuracy, low sampling rate and strong anti-noise performance.