基于压缩感知的MIMO-SAR运动误差补偿与成像
收稿日期: 2013-05-29
修回日期: 2013-10-08
网络出版日期: 2013-10-12
基金资助
国家“973”计划（2010CB731905）；国家自然科学基金（61201369）；陕西省自然科学基金（2013JQ8008）；广西无线宽带通信与信号处理重点实验室2011年度开放基金项目（21102）；空军工程大学信息与导航学院博士生创新基金
Motion Error Compensation and Imaging for MIMO-SAR Based on Compressed Sensing
Received date: 2013-05-29
Revised date: 2013-10-08
Online published: 2013-10-12
Supported by
National Basic Research Program of China (2010CB731905); National Natural Science Foundation of China (61201369); Natural Science Foundation of Shaanxi Province (2013JQ8008); The Foundation of Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing (21102); The Doctoral Foundation of Information and Navigation Institute, Air Force Engineering University
多发多收合成孔径雷达（MIMO-SAR）利用多通道空间并行采样的优势可实现高分辨成像，但不可避免地存在运动误差与海量数据不便于存储与传输的问题。针对该问题提出一种基于压缩感知的MIMO-SAR运动误差补偿与成像方法。首先通过详细分析MIMO-SAR运动误差回波信号模型，在全采样条件下利用两步运动补偿技术实现对回波数据的运动误差补偿处理，其次针对降采样回波数据的运动误差补偿，通过构造变换算子与压缩感知（CS）重构模型的方法实现第1步运动误差补偿、距离脉压以及距离徙动校正处理，然后再进行第2步误差补偿与方位向脉压处理获得成像结果。最后通过仿真实验验证了所提方法能够在大幅压缩回波数据的情况下，实现MIMO-SAR运动误差补偿与成像处理。
关键词： 多发多收合成孔径雷达; 压缩感知; 运动误差; 两步补偿; 变换算子
顾福飞 , 张群 , 管桦 , 杨秋 , 彭发祥 . 基于压缩感知的MIMO-SAR运动误差补偿与成像[J]. 航空学报, 2014 , 35(3) : 838 -847 . DOI: 10.7527/S1000-6893.2013.0410
Multiple-input multiple-output synthetic aperture radar (MIMO-SAR) can realize high resolution imaging by its predominance of the multichannel spatial parallel sampling, but the inevitable problems of motion compensation and huge amount of echo data need to be resolved. A novel motion error compensation and imaging method for MIMO-SAR based on compressed sensing (CS) is proposed. Firstly, the echo signal model of MIMO-SAR system with motion error is analyzed and the motion error of the Nyquist-sampled data is corrected by the two steps of compensation. Secondly, in order to compensate the motion error of the under-sampled echo signal, the transform operator is constructed, which could realize the first step of compensation, range compression and range migration correction processing. At last, the imaging result is obtained by the second step of compensation and azimuth compression. The effectiveness of the proposed method is proved by the imaging simulations. By using the proposed method, just a small amount of imaging data is required for MIMO-SAR motion error compensation and imaging.
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