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Volume 33 Issue 1
Feb.  2011
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Wang Guang-Xue, Huang Xiao-Tao, Zhou Zhi-Min. UWB SAR Change Detection of Target in Foliage Based on Local Statistic Distribution Change Analysis[J]. Journal of Electronics & Information Technology, 2011, 33(1): 49-54. doi: 10.3724/SP.J.1146.2010.00202
Citation: Wang Guang-Xue, Huang Xiao-Tao, Zhou Zhi-Min. UWB SAR Change Detection of Target in Foliage Based on Local Statistic Distribution Change Analysis[J]. Journal of Electronics & Information Technology, 2011, 33(1): 49-54. doi: 10.3724/SP.J.1146.2010.00202

UWB SAR Change Detection of Target in Foliage Based on Local Statistic Distribution Change Analysis

doi: 10.3724/SP.J.1146.2010.00202
  • Received Date: 2010-03-09
  • Rev Recd Date: 2010-07-05
  • Publish Date: 2011-01-19
  • Because of large pixel value change between multitemporal UWB SAR images caused by different imaging geometries, the performance of change detection algorithm based on pixel value difference declines quickly. In order to deal with this problem, a new UWB SAR foliage target change detection algorithm based on local statistic distribution is proposed. In the algorithm, the Gram-Charlier expansion theory and rank order filter are combined to estimate local statistic distribution. Then, the K-L divergence is used to measure the change between local statistic distribution of multitemporal UWB SAR image. And the target can be detected because of large K-L divergence value. Finally, the experimental results show that the algorithm can better deal with the pixel value change between multitemporal UWB SAR images with different imaging geometries and an obvious performance improvement on detection can be obtained.
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  • 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],长沙:国防科技大学, 2007: 17-23.[2]Ulander M H. Modeling of change detection in VHF- and UHF-band SAR [C]. EUSAR2008, Fridrichshafen, 2008, 2: 127-131.[3]Novak L. Target recognition and polarimetric SAR[R]. Tutorial of 2008 IEEE Radar Conference, Rome, 2008, Tutorial #13.[4]Novak L. Algorithms for SAR Change Detection, Compression and super-resolution[R]. Tutorial of 2009 International Radar Conference, 2009, Bordeaux, Tutorial #10.[5]Lundberg M, Ulander M H, Pierson E, and Gustavsson A. A challenge problem for detection of targets in foliage[C]. Conference on Algorithms for Synthetic Aperture Radar Imagery, Orlando, 2006, SPIE 6237: 1-12.[6]Lundberg M, Ulander M H, PiersonE, and Gustavsson A. Change detection for low-frequency SAR ground surveillance[J].IEE Prodeedings Radar sonar and navigation.2005, 152(6):413-420[7]杨志国, 黄小涛, 周智敏. SAR目标检测中的一种稳健变化检测算法[J].电子与信息学报.2008, 30(9):2094-2098浏览[8]Cavalcante C C, Mota C M, and Romano M T. Polynomial expansion of the probability density function about gaussian mixtures [C]. IEEE Workshop on machine learning for signal processing, Sao Luis, 2004: 163-172.[9]Haykin S. Neural Network: A Comprehensive Foundation. 2nd Edition[M]. New Jersey: Prentice Hall, New Jersey, 1999: 566-567.[10]FOI. CARABAS-II VHF SAR data set[DB/OL], Http:// www. sdms. afrl.af.mil/datasets, 2005.[11]Fung T and Ledrew E. The determination of optimal threshold levels for changes detection using various accuracy indices[J]. Photogrammetric Engineering and Remote Sensing, 1988, 54(10): 1449-1454.
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