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一种新的SAR窄带干扰抑制方法 被引量:5

New method for SAR narrowband interference suppression
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摘要 合成孔径雷达易受电视网、通信网等无线设备的电磁干扰,严重影响成像质量。本文在分析SAR受到的干扰特点和信号模型的基础上,提出了一种基于压缩感知的SAR窄带干扰抑制方法。该方法根据SAR回波信号和窄带干扰信号在Chirplet字典上的调频斜率参数不同,在SAR回波信号重构过程中对干扰信号进行筛选并抑制,再把去除干扰后的压缩数据利用常规SAR成像算法进行成像。仿真结果表明,该方法不仅能有效抑制窄带干扰,而且大大减少了SAR系统成像处理的数据量,验证了本文所提方法的有效性。 Synthetic aperture radar is susceptible to electromagnetic interference by television networks,communication networks and other wireless devices,which seriously damages the image quality.Under the premise of the analysis of the characteristics of interference and signal model,a method of SAR narrowband interference suppression based on compressed sensing was proposed.According to the difference of the FM slope of the SAR echo signal and the narrowband interference signals in the Chirplet dictionary,interference signal was filtrated and suppressed in the reconstruction of the SAR echo signal,and then use the conventional method to achieve the SAR image with the compressed data in which the disturbance is removed away.The simulation results show that the method not only can effectively suppresses narrowband interference,but also greatly reduces the amount of data in SAR imaging processing system,which demonstrate the effectiveness of the proposed method.
出处 《国外电子测量技术》 2016年第1期44-48,共5页 Foreign Electronic Measurement Technology
关键词 合成孔径雷达 窄带干扰抑制 压缩感知 Chirplet字典 调频斜率 synthetic aperture radar narrowband interference suppression compressed sensing Chirplet dictionary FM slope
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  • 1周峰,邢孟道,保铮.基于特征子空间滤波的SAR窄带干扰抑制方法[J].电子与信息学报,2005,27(5):767-770. 被引量:11
  • 2张春梅,尹忠科,肖明霞.基于冗余字典的信号超完备表示与稀疏分解[J].科学通报,2006,51(6):628-633. 被引量:70
  • 3孙佳.国外合成孔径雷达卫星发展趋势分析[J].装备指挥技术学院学报,2007,18(1):67-70. 被引量:19
  • 4R Baraniuk.A lecture on compressive sensing[J].IEEE Signal Processing Magazine,2007,24(4):118-121.
  • 5Guangming Shi,Jie Lin,Xuyang Chen,Fei Qi,Danhua Liu and Li Zhang.UWB echo signal detection with ultra low rate sampling based on compressed sensing[J].IEEE Trans.On Circuits and Systems-Ⅱ:Express Briefs,2008,55(4):379-383.
  • 6Cand,S E J.Ridgelets:theory and applications[I)].Stanford.Stanford University.1998.
  • 7E Candès,D L Donoho.Curvelets[R].USA:Department of Statistics,Stanford University.1999.
  • 8E L Pennec,S Mallat.Image compression with geometrical wavelets[A].Proc.of IEEE International Conference on Image Processing,ICIP'2000[C].Vancouver,BC:IEEE Computer Society,2000.1:661-664.
  • 9Do,Minh N,Vetterli,Martin.Contourlets:A new directional multiresolution image representation[A].Conference Record of the Asilomar Conference on Signals,Systems and Computers[C].Pacific Groove,CA,United States:IEEE Computer Society.2002.1:497-501.
  • 10G Peyré.Best Basis compressed sensing[J].Lecture Notes in Ccmputer Science,2007,4485:80-91.

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