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压缩感知理论在频率步进探地雷达偏移成像中的应用

屈乐乐 方广有 杨天虹

屈乐乐, 方广有, 杨天虹. 压缩感知理论在频率步进探地雷达偏移成像中的应用[J]. 电子与信息学报, 2011, 33(1): 21-26. doi: 10.3724/SP.J.1146.2009.01528
引用本文: 屈乐乐, 方广有, 杨天虹. 压缩感知理论在频率步进探地雷达偏移成像中的应用[J]. 电子与信息学报, 2011, 33(1): 21-26. doi: 10.3724/SP.J.1146.2009.01528
Qu Le-Le, Fang Guang-You, Yang Tian-Hong. The Application of Compressed Sensing to Stepped-frequency Ground Penetrating Radar Migration Imaging[J]. Journal of Electronics & Information Technology, 2011, 33(1): 21-26. doi: 10.3724/SP.J.1146.2009.01528
Citation: Qu Le-Le, Fang Guang-You, Yang Tian-Hong. The Application of Compressed Sensing to Stepped-frequency Ground Penetrating Radar Migration Imaging[J]. Journal of Electronics & Information Technology, 2011, 33(1): 21-26. doi: 10.3724/SP.J.1146.2009.01528

压缩感知理论在频率步进探地雷达偏移成像中的应用

doi: 10.3724/SP.J.1146.2009.01528
基金项目: 

国家863计划项目(2007AA12Z124)资助课题

The Application of Compressed Sensing to Stepped-frequency Ground Penetrating Radar Migration Imaging

  • 摘要: 该文针对频率步进探地雷达的具体工作过程,利用目标成像空间的稀疏性提出了一种基于压缩感知理论的频率步进探地雷达偏移成像算法,成像过程中首先采用杂波抑制方法在频率域去除直达波,同时利用交叉验证算法来估计成像过程中的正则化参数,最后基于稀疏约束最优化方法实现对地下目标成像,仿真和实验数据表明了该算法的可行性和有效性。
  • 粟毅, 黄春琳, 雷文太. 探地雷达理论及应用[M]. 北京: 科学出版社, 2006: 1-3.[2]方广有, 佐藤源之. 频率步进探地雷达及其在地雷探测中的应用[J]. 电子学报, 2005, 33(3): 436-439.Fang Guang-you and Sato Motoyuki. Stepped frequency ground penetrating radar and its application for landmine detection[J]. Acta Electronica Sinica, 2005, 33(3): 436-439.[3]Fang Guang-you. The research activities of ultrawide- band(UWB) radar in China[C]. IEEE International Conference on Ultra-Wideband, Singapore, 2007: 43-45.[4]Donoho D L. Compressed sensing[J].IEEE Transactions on Information Theory.2006, 52(4):1289-1306[5]Candes E J and Wakin M B. An introduction to compressive sampling[J].IEEE Signal Processing Magazine.2008, 25(2):21-30[6]石光明, 刘丹华, 高大化等. 压缩感知理论及其研究进展[J]. 电子学报, 2009, 27(5): 1070-1081.[7]Shi Guang-ming, Liu Dan-huang, and Gao Da-hua, et al.. Advances in theory and applications of compressed sensing[J]. Acta Electronica Sinica, 2009, 37(5): 1070-1081.[8]Romberg J. Imaging via compressive sampling[J]. IEEE Signal Processing Magazine, 2008, 25(2): 14-20.[9]Ma J W. Single-pixel remote sensing[J].IEEE Geoscience and Remote Sensing Letters.2009, 6(2):199-203[10]Herman M A and Strohmer T. High-resolution radar via compressed sensing[J].IEEE Transactions on Signal Processing.2009, 57(6):2275-2284[11]Gurbuz A C, McClellan J H, and Scott W R. A compressive sensing data acquisition and imaging method for stepped frequency GPRs[J].IEEE Transactions on Signal Processing.2009, 57(7):2640-2650[12]Johansson E M and Mast J E. Three dimensional ground penetrating radar imaging using a synthetic aperture time-domain focusing[C]. Proc of SPIE Conference on Advanced Microwave and Millimeter Wave Detectors. San Diego, 1994: 205-214.[13]Candes E and Tao T. The dantzig selector: statistical estimation when p is much larger than n[J].The Annals of Statistics.2007, 35(6):1-41[14]Boufounos P, Duarte M F, and Baraniuk R G. Sparse signal reconstruction from noisy compressive measurements using cross validation[C]. IEEE Workshop on Statistical Signal Processing. Madison: 2007: 200-303.[15]Wu R and Clement J, et al.. Adaptive ground bounce removal[J].Electronic Letters.2001, 37(2):1250-1252
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出版历程
  • 收稿日期:  2009-12-01
  • 修回日期:  2010-09-09
  • 刊出日期:  2011-01-19

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