一种适用于FLGPSAR的自适应干扰抑制与背景均衡新方法

杨延光; 宋千; 金添; 王建; 周智敏

doi:10.3724/SP.J.1146.2008.00276

一种适用于FLGPSAR的自适应干扰抑制与背景均衡新方法

doi: 10.3724/SP.J.1146.2008.00276

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出版历程
- 收稿日期: 2008-03-17
- 修回日期: 2009-01-19
- 刊出日期: 2009-07-19

A Novel Adaptive Interferences Suppression and Background Uniformization Method Applicable to FLGPSAR System

摘要

摘要: 针对车载前视地表穿透合成孔径雷达(Forward-Looking Ground Penetrating Synthetic Aperture Radar, FLGPSAR)探测系统存在自信号干扰和图像背景增益不一致问题，该文提出了一种基于图像域距离带分割和迭代操作的自适应干扰抑制和背景均衡新方法。通过距离带分割实现并行处理并提高参数估计的准确性，采用迭代操作在线估计和更新参数，自适应实现干扰去除和图像背景增益均衡。实测数据处理结果表明：所提方法具有更好的环境适应性，且结构上适于实时处理，可满足车载FLGPSAR探测系统对图像预处理的需求。
- 探地雷达(GPR);合成孔径雷达(SAR);图像预处理;自适应干扰抑制;距离带分割;迭代操作
Abstract: To solve the problems of the self-signature interference and the nonuniformity of image background existing in the vehicle-mounted Forward-Looking Ground Penetrating Synthetic Aperture Radar (FLGPSAR) detection system, an adaptive method is proposed to realize interferences suppression and background uniformization based on distance-band partition and iterative operation techniques in the image domain. Parallel processing can be realized via distance-band partition, which can also improve the accuracy of parameters estimation. Parameters can be estimated and updated on line by using the iterative operation technique, and then the interference suppression and background gain uniformization can be adaptively achieved. Experimental results of the real data show that proposed method has a better adaptability to environment and is prone to real-time processing in structure. It can effectively meet the needs of the vehicle-mounted FLGPSAR system for image preprocessing.

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金添. 超宽带SAR 浅埋目标成像与检测的理论和技术研究[D].[博士论文], 国防科技大学, 2007.Jin Tian. Research on theory and technique of ultra-wideband SAR shallow buried targets imaging and detection[D]. [Ph.D. dissertation], National University of DefenseTechnology, 2007.[2]Sun Y J and Li J. Adaptive learning approach to landminedetection[J].IEEE Transactions on Aerospace and ElectronicSystems.2005, 41(3):973-985[3]Nguyen L, Ton T, and Wong D, et al.. Signal processingtechniques for forward imaging using ultra-wideband syntheticaperture radar[J].Proceedings of SPIE.2003, 5083:505-518[4]Kositsky J, Cosgrove R, and Amazeen C, et al.. Results froma forward-looking GPR mine detection system[J].Proceedingsof SPIE.2002, 4742:206-217[5]Cosgrove R B, Milanfar P, and Kositsky J. Trained detectionof buried mines in SAR images via the deflection-optimalcriterion[J].IEEE Transactions on Geoscience and RemoteSensing.2004, 42(11):2569-2575[6]Bradley M, Witten T, and Duncan M, et al.. Mine detectionwith a forward-looking ground-penetrating synthetic apertureradar[J].Proceedings of SPIE.2003, 5089:334-347[7]Delmote P, Dubois C, and Andrieu J, et al.. The UWB SARsystem Pulsar: New generator and antenna developments[J].Proceedings of SPIE.2003, 5077:223-234[8]杨延光, 周智敏, 宋千. 分裂孔径发射阵列接收BP 算法方位分辨率分析. 信号处理, 2008, 24(5): 752-756.Yang Yan-guang, Zhou Zhi-min, and Song Qian. Azimuthresolution analysis of back-projection algorithm with the splitaperture transmit configuration antenna system. SignalProcessing, 2008, 24(5): 752-756.[9]Gu K L, Wang G, and Li J. Migration based SAR imaging forground-penetrating radar systems[J].Proceedings of SPIE.2003, 5095:33-44[10]Wang T, Sjahputera O, and Keller J M, et al.. Featureanalysis for forward-looking landmine detection using GPR[J].Proceedings of SPIE.2005, 5794:1233-1244[11]Ulander L M H, Hellsten H, and Stenstrom G. Synthetic-aperture radar processing using fast factorizedback-projection[J].IEEE Transactions on Aerospace and ElectronicSystems.2003, 39(3):760-776[12]杨志国. 基于ROI 的UWB SAR 叶簇覆盖目标鉴别方法研究[D]. [博士论文], 国防科技大学, 2007.Yang Zhi-guo. Foliage-concealed target discrimination ofUWB SAR based on ROI[D]. [Ph.D. dissertation], NationalUniversity of Defense Technology, 2007.

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