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基于压缩感知的二维雷达成像算法

谢晓春 张云华

谢晓春, 张云华. 基于压缩感知的二维雷达成像算法[J]. 电子与信息学报, 2010, 32(5): 1234-1238. doi: 10.3724/SP.J.1146.2009.01223
引用本文: 谢晓春, 张云华. 基于压缩感知的二维雷达成像算法[J]. 电子与信息学报, 2010, 32(5): 1234-1238. doi: 10.3724/SP.J.1146.2009.01223
Xie Xiao-chun, Zhang Yun-hua. 2D Radar Imaging Scheme Based on Compressive Sensing Technique[J]. Journal of Electronics & Information Technology, 2010, 32(5): 1234-1238. doi: 10.3724/SP.J.1146.2009.01223
Citation: Xie Xiao-chun, Zhang Yun-hua. 2D Radar Imaging Scheme Based on Compressive Sensing Technique[J]. Journal of Electronics & Information Technology, 2010, 32(5): 1234-1238. doi: 10.3724/SP.J.1146.2009.01223

基于压缩感知的二维雷达成像算法

doi: 10.3724/SP.J.1146.2009.01223

2D Radar Imaging Scheme Based on Compressive Sensing Technique

  • 摘要: 压缩感知理论能够有效地降低高分辨率雷达成像系统的数据率。该文通过对复基带雷达回波信号模型的稀疏性分析,提出了一种具有保相性的压缩感知距离压缩算法。在此基础上建立了距离向采用压缩感知距离压缩算法,方位向采用传统的雷达成像算法处理的雷达2维成像方案。通过对仿真和实测逆合成孔径雷达数据的成像处理验证了方案的有效性。
  • Tsaig Y and Donoho D L. Extensions of compressed sensing[J].Signal Processing.2006, 86(3):549-571[2]Candes E J, Romberg J, and Tao T. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information[J].IEEE Transactions on Information Theory.2006, 52(2):489-509[3]Baraniuk R and Steeghs P. Compressive radar imaging[C]. IEEE Radar Conference, Boston, MA, USA, Apr.17-20, 2007: 128-133.[4]Herman M and Strohmer T. Compressed sensing radar[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, Las Vegas, NV, USA, Mar.30-Apr.4, 2008: 1509-1512.[5]Yoon Y S and Amin M G. Compressed sensing technique for high-resolution radar imaging [J]. Proceedings of the SPIE, 2008, Vol.6968: 69681A-69681A-10.[6]Varshney K R, Cetin M, and Fisher J W, et al.. Sparse representation in structured dictionaries with application to synthetic aperture radar[J].IEEE Transactions on Signal Processing.2008, 56(8):3548-3561[7]Potter L C, Schniter P, and Ziniel J. Sparse reconstruction for radar[J].Proceedings of the SPIE.2008, Vol.6970:697003-697003[8]Tello M, Lopez-Dekker P, and Mallorqui J J. A novel strategy for radar imaging based on compressive sensing[C]. International Geoscience and Remote Sensing Symposium, Boston, MA, USA, Jul.7-11, 2008, Vol.2: II-213-II-216.[9]Gurbuz A C, Mcclellan J H, and Scott W R Jr. GPR imaging using compressed measurements[C]. International Geoscience and Remote Sensing Symposium, International Geoscience and Remote Sensing Symposium, Boston, MA, USA, Jul.7-11, 2008, Vol.2: II-13-II-16.[10]Lin Yun, Hong Wen, and Tan Wei-xian, et al.. Compressed sensing technique for circular SAR imaging[C]. IET International Radar Conference, Guilin, China, Apr.20-22, 2009: 676-679.[11]Lei Z, Mengdao X, and Cheng-Wei Q, 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[12]Shi G M, Lin J, and Chen X Y, et al.. UWB echo signal detection with ultra-low rate sampling based on compressed sensing[J].IEEE Transactions on Circuits and Systems II-Express Briefs.2008, 55(4):379-383[13]Jouny I. Compressed sensing for UWB radar target signature reconstruction[C]. Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, Marco Island, FL, USA, Jan.4-7, 2009: 714-719.[14]Sami K, Jason L, and Michael W, et al.. Analog-to- Information conversion via random demodulation[C]. IEEE Dallas Circuits and Systems Workshop, Dallas, Tex, USA, Oct.29-30, 2006: 71-74.[15]Ji S H, Xue Y, and Carin L. Bayesian compressive sensing[J].IEEE Transactions on Signal Processing.2008, 56(6):2346-2356[16]Zhang Yun-hua.[J].Zhang Xiang-kun, and Zhai Wen-shuai, et al.. Moving train imaging by ground-based Ka-band radar[C]. Loughborough Antennas Propagation Conference 2009, Loughborough, UK, Nov.16-1.2009,:-
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出版历程
  • 收稿日期:  2009-09-15
  • 修回日期:  2010-02-09
  • 刊出日期:  2010-05-19

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