期刊文献+

基于压缩感知的双通道SAR地面运动目标检测方法研究 被引量:6

A Compressive Sensing Based SAR GMTI Method for Dual-channel SAR System
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摘要 针对目前双通道SAR地面运动目标检测(GMTI)方法采样数据量过大的问题,该文提出一种基于压缩感知的双通道SAR运动目标检测方法。该方法首先沿方位向进行随机稀疏采样得到双通道原始回波数据,然后通过匹配滤波方法实现距离向聚焦,并利用压缩感知技术实现方位聚焦,最后运用传统相位中心偏置天线(DPCA)技术进行杂波抑制。通过公式推导从理论上分析了该算法利用双通道方位稀疏采样数据实现杂波抑制的可行性,同时详细分析了运动参数对目标成像的影响。仿真与实测数据实验表明该算法在方位向欠采样情况下仍具有良好的杂波抑制性能。 In the conventional SAR Ground Moving Targets Indication(GMTI) method,the sample number is heavily large,increasing severely data transmission and storage load.To mitigate this problem,a SAR GMTI method is proposed based on Compressive Sensing(CS) in this paper.In the presented method,raw radar data of dual channels are firstly acquired by sampling randomly and sparsely in the azimuth direction.Secondly,the matched filter is used to perform the range direction focus and compressive sensing method is used to perform the azimuth direction focus.Finally,the conventional Displaced Phase Center Antenna(DPCA) technique is adopted to suppress clutter.Theoretical analysis shows that the proposed method can be applied to clutter suppression of the sparse sampling data of dual channels and the effects of motion parameters on target imaging are analysed in detail.The results of simulated and real data processing verify that the proposed method has excellent clutter suppression performance even if few samples can be obtained in the azimuth direction.
出处 《电子与信息学报》 EI CSCD 北大核心 2012年第3期587-593,共7页 Journal of Electronics & Information Technology
基金 国家973计划项目(2010CB731903) 国家杰出青年科学基金(60825104) 国家自然科学基金(61101249)资助课题
关键词 合成孔径雷达 稀疏采样 压缩感知 地面运动目标检测 SAR Sparse sampling Compressive Sensing(CS) Ground Moving Target Indication(GMTI)
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参考文献15

  • 1Wang H S C.Mainlobe clutter cancellation by DPCA forspace-based radars[C].IEEE Aerospace ApplicationsConference Digest,Crested Butte,USA,Feb.1991:1-10. 被引量:1
  • 2郑明洁,杨汝良.基于DPCA和干涉技术的SAR动目标检测[J].电子与信息学报,2003,25(11):1525-1530. 被引量:23
  • 3Pascazio V,Schirinzi V,and Farina A.Moving targetdetection by along-track interferometry[C].InternationalGeoscience and Remote Sensing Symposium(IGARSS),Sydney,AUS,2001:3024-3026. 被引量:1
  • 4Sikaneta I and Gierull C H.Ground moving target detectionfor along-track interferometric SAR data[C].IEEE AerospaceConference,Big Sky,USA,March,2004:2227-2235. 被引量:1
  • 5Candes E J,Romberg J,and Tao T.Robust uncertaintyprinciples:exact signal reconstruction from highly incompletefrequency information[J].IEEE Transactions onInformation Theory,2006,52(2):489-509. 被引量:1
  • 6Candes E J and Tao T.Near optimal signal recovery fromrandom projections:universal encoding strategies?[J].IEEETransactions on Information Theory,2006,52(12):5406-5425. 被引量:1
  • 7Donoho D L,Elad M,and Temlyakov V N.Stable recovery ofsparse overcomplete representations in the presence of noise[J].IEEE Transactions on Information Theory,2006,52(1):6-18. 被引量:1
  • 8Donoho D L.Compressed sensing[J].IEEE Transactions onInformation Theory,2006,52(4):1289-1306. 被引量:1
  • 9Zhang Lei,Xing Meng-dao and Qiu Cheng-wei.Resolutionenhancement for inversed synthetic aperture radar imagingunder low SNR via improved compressive sensing[J].IEEETransactions on Geoscience and Remote Sensing,2010,48(10):3824-3838. 被引量:1
  • 10Huang Q,Qu L L,Wu B H,et al..UWB through-wallimaging based on compressive sensing[J].IEEE Transactionson Geoscience and Remote Sensing,2010,48(3):1408-1415. 被引量:1

二级参考文献18

  • 1Tsaig Y and Donoho D L.Extensions of compressed sensing[J].Signal Processing,2006,86(3):549-571. 被引量:1
  • 2Candes 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. 被引量:1
  • 3Baraniuk R and Steeghs P.Compressive radar imaging[C].IEEE Radar Conference,Boston,MA,USA,Apr.17-20,2007:128-133. 被引量:1
  • 4Herman 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. 被引量:1
  • 5Yoon 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. 被引量:1
  • 6Varshney 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. 被引量:1
  • 7Potter L C,Schniter P,and Ziniel J.Sparse reconstruction for radar[J].Proceedings of the SPIE,2008,Vol.6970:697003-697003-15. 被引量:1
  • 8Tello 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. 被引量:1
  • 9Gurbuz 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. 被引量:1
  • 10Lin 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. 被引量:1

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