ACTA AERONAUTICAET ASTRONAUTICA SINICA >
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
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.
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 . DOI: 10.7527/S1000-6893.2013.0410
[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.
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