基于压缩感知的MIMO-SAR运动误差补偿与成像

doi:10.7527/S1000-6893.2013.0410

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基于压缩感知的MIMO-SAR运动误差补偿与成像

顾福飞¹, 张群¹, 管桦¹, 杨秋¹, 彭发祥²

1. 空军工程大学信息与导航学院, 陕西西安 710077;
2. 中国人民解放军 95261部队, 广西柳州 545000

收稿日期:2013-05-29 修回日期:2013-10-08 出版日期:2014-03-25 发布日期:2013-10-12
通讯作者: 张群，Tel.：029-84791751 E-mail：zhangqunnus@gmail.com E-mail:zhangqunnus@gmail.com
作者简介:顾福飞男，博士研究生。主要研究方向：雷达成像与压缩感知理论。Email：gffpan@126.com；张群男，博士，教授，博士生导师。主要研究方向：雷达信号与信息处理、雷达成像。Tel：029-84791751 E-mail：zhangqunnus@gmail.com
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

GU Fufei¹, ZHANG Qun¹, GUAN Hua¹, YANG Qiu¹, PENG Faxiang²

1. School of Information and Navigation, Air Force Engineering University, Xi'an 710077, China;
2. Unit 95261, the Chinese People's Liberation Army, Liuzhou 545000, China

Received:2013-05-29 Revised:2013-10-08 Online:2014-03-25 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

摘要/Abstract

摘要：

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

Abstract:

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.

Key words: MIMO-SAR, compressed sensing, motion error, two steps of compensation, transform operator

中图分类号:

V243.2
TN957

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.

GU Fufei, ZHANG Qun, GUAN Hua, YANG Qiu, PENG Faxiang. Motion Error Compensation and Imaging for MIMO-SAR Based on Compressed Sensing[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014, 35(3): 838-847.

参考文献

[1] Wu Q S, Jing W, Xing M D, et al. Wide swath imaging with MIMO-SAR [J]. Journal of Electronics & Information Technology, 2009, 31(4): 771-775. (in Chinese) 武其松, 井伟, 邢孟道, 等. MIMO-SAR大测绘带成像 [J]. 电子与信息学报, 2009, 31(4): 771-775.

[2] Ender J H G, Klare J. System architectures and algorithms for radar imaging by MIMO-SAR [C]//Radar Conference, IEEE, 2009: 1-6.

[3] Huang P P, Deng Y K, Xu W, et al. The research of multiple-input and multiple-output SAR based on frequency synthetic [J]. Journal of Electronics & Information Technology, 2011, 33(2): 401-406. (in Chinese) 黄平平, 邓云凯, 徐伟, 等. 基于频域合成方法的多发多收SAR技术研究[J]. 电子与信息学报, 2011, 33(2): 401-406.

[4] Wang W, Wang X P, Ma Y H. Multi-target localization based on multi-stage wiener filter for bistatic MIMO radar[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(7): 1281-1288. (in Chinese) 王伟, 王咸鹏, 马跃华. 基于多级维纳滤波的双基地MIMO雷达多目标定位方法[J]. 航空学报, 2012, 33(7): 1281-1288.

[5] Peng F X, Li H W, Cai B, et al. An imaging method of high resolution airborne MIMO-SAR based on motion compensation [J]. Journal of Air Force Engineering University: Natural Science Edition, 2012, 13(1): 73-78. (in Chinese) 彭发祥, 李宏伟, 蔡斌, 等. 基于运动补偿的机载MIMO-SAR高分辨成像算法 [J]. 空军工程大学学报: 自然科学版, 2012, 13(1): 73-78.

[6] Donoho D L. Compressed sensing [J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.

[7] Candes E J, Tao T. Near-optimal signal recovery from random projections: universal encoding strategies [J]. IEEE Transactions on Information Theory, 2006, 52(12): 5406-5425.

[8] Zhang L, Xing M D, Qiu C W, et al. Achieving higher resolution ISAR imaging with limited pulses via compressed sampling [J]. IEEE Geoscience and Remote Sensing Letters, 2009, 6(3): 567-571.

[9] Herman M A, Strohmer T. High-resolution radar via compressed sensing [J]. IEEE Transactions on Signal Processing, 2009, 57(6): 2275-2284.

[10] Patel V M, Easley G R, Healy, et al. Compressed synthetic aperture radar [J]. IEEE Journal of Selected Topics in Signal Process, 2010, 4(2): 244-254.

[11] Chang J F, Zhang S S. Study on multi-transmit and multi-receive high resolution SAR imaging algorithm based on compressive sensing [J]. Fire Control Radar Technology, 2011, 40(4): 25-31. (in Chinese) 常俊飞, 张顺生. 基于压缩感知的多发多收高分辨SAR成像算法研究[J]. 火控雷达技术, 2011, 40(4): 25-31.

[12] Liu B, Han C L, Miao J H. OFD-LFM signal design and performance analysis for MIMO radar [J]. Journal of University of Electronic Science and Technology of China, 2009, 38(1): 28-31. (in Chinese) 刘波, 韩春林, 苗江宏. MIMO雷达正交频分LFM信号设计及性能分析 [J]. 电子科技大学学报, 2009, 38(1): 28-31.

[13] Giorgio F, Riccardo L. Synthetic aperture radar processing[M]. Washington, D.C.: CRC Press, 1999.

[14] Wang L B, Xu J, Huangfu K, et al. Analysis and compensation of equivalent phase center error in MIMO-SAR [J]. Acta Electronica Sinica, 2009, 37(12): 2688-2693. (in Chinese) 王力宝, 许稼, 皇甫堪, 等. MIMO-SAR等效相位中心误差分析与补偿 [J]. 电子学报, 2009, 37(12): 2688-2693.

[15] Bao Z, Xing M D, Wang T. Radar imaging technology [M]. Beijing: Publishing House of Electronics Industry, 2005: 200-208. (in Chinese) 保铮, 邢孟道, 王彤. 雷达成像技术 [M]. 北京: 电子工业出版社, 2005: 200-208.

[16] Candés E. The restricted isometry property and its implications for compressed sensing [J]. Comptes Rendus Mathematic, 2006, 246 (9): 589-592.

[17] Baraniuk R. A lecture on compressive sensing [J]. IEEE Signal Processing Magazine, 2007, 24(4): 118-121.

[18] Mohimani G H, Babaie-Zadeh M, Jutten C. A fast approach for overcomplete sparse decomposition based on smoothed norm [J]. IEEE Transactions on Signal Processing, 2009, 57(1): 289-301.

[19] Tropp J A, Wakin M B, Duarte M F, et al. Random filters for compressive sampling and reconstruction [C]//Processing of the International Conference on Acoustics, Speech and Signal Processing, 2006.

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于压缩感知的MIMO-SAR运动误差补偿与成像

Motion Error Compensation and Imaging for MIMO-SAR Based on Compressed Sensing

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