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基于微多普勒特征的坦克目标参数估计与身份识别

黄健 李欣 黄晓涛 贺峰

黄健, 李欣, 黄晓涛, 贺峰. 基于微多普勒特征的坦克目标参数估计与身份识别[J]. 电子与信息学报, 2010, 32(5): 1050-1055. doi: 10.3724/SP.J.1146.2009.00669
引用本文: 黄健, 李欣, 黄晓涛, 贺峰. 基于微多普勒特征的坦克目标参数估计与身份识别[J]. 电子与信息学报, 2010, 32(5): 1050-1055. doi: 10.3724/SP.J.1146.2009.00669
Huang Jian, Li Xin, Huang Xiao-tao, He Feng. Micro-Doppler Features Based Parameter Estimation and Identification of Tank[J]. Journal of Electronics & Information Technology, 2010, 32(5): 1050-1055. doi: 10.3724/SP.J.1146.2009.00669
Citation: Huang Jian, Li Xin, Huang Xiao-tao, He Feng. Micro-Doppler Features Based Parameter Estimation and Identification of Tank[J]. Journal of Electronics & Information Technology, 2010, 32(5): 1050-1055. doi: 10.3724/SP.J.1146.2009.00669

基于微多普勒特征的坦克目标参数估计与身份识别

doi: 10.3724/SP.J.1146.2009.00669

Micro-Doppler Features Based Parameter Estimation and Identification of Tank

  • 摘要: 对坦克装甲车等地面活动目标进行分类与精确识别具有重要意义。微多普勒特征能反映目标的多种细微特征,在目标身份识别上具有独特优势。该文讨论了坦克目标炮塔炮管这样特有结构的微多普勒特征,基于不同种类和型号的坦克目标炮塔激励的不同微多普勒特征,提出了一种对坦克目标参数估计和精确身份识别的方法并给出一般步骤。给出了微多普勒的理论计算和仿真时频谱,仿真结果验证了理论分析与方法的正确性。为已有目标识别方法提供了重要辅助手段。
  • Li Y, Liu H W, and Bao Z. Radar HRRP recognition based on the minimum Kullback Leibler distance criterion[J].Journal of Electronics (China.2007, 24(2):199-203[2]高倩, 刘家学, 吴仁彪. 一种基于高分辨率距离像自动目标识别新方法[J]. 中国民航学院学报, 2002, 20(1): 1-4.[3]Gao Qian, Liu Jia-xue, and Wu Ren-biao. Novel method for automatic target recognition based on high resolution range profiles[J]. Journal of Civil Aviation University of China,[4]02, 20(1): 1-4.[5]Guo W, Qi Q, Jiang L L, and Zhang P. A new method of SAR image target recognition based on AdaBoost algorithm[C]. IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Boston, Massachusetts, July, 2008, III: 1194-1197.[6]Tong L B, Lu W J, and Qi D N, et al.. Target recognition based on seismic sensors and neural network[C][J].The Eighth International Conference on Electronic Measurement and Instruments, ICEMI2007, Xian.2007, 1:18-21[7]Smith G E, Woodbridge K, and Baker C J. Template based micro-Doppler signature classification[C]. Radar Conference, Manchester, UK. 3rd European, Sept., 2006: 158-161.[8]Stove A G and Sykes S R. A Doppler-based automatic target classifier for a battlefield surveillance radar[C]. Proceedings of IEEE International Conference on Radar, Edinburgh, UK, October, 2002: 419-423.[9]Kulpa K. Advances in Sensing with Security Applications: Continuous Wave Radars-monostatic, Multistatic and Network[M]. ser. NATO Security through Science Series, Netherlands: Springer, 2006: 215-242.[10]Ghaleb A, Vignaud L, and Nicolas J M. Micro-Doppler analysis of wheels and pedestrians in ISAR imaging[J].IET Signal Process.2008, 2(3):301-311[11]Tan H S, Ma C Z, and Yeo T S, et al.. ISAR imaging of targets with moving parts using micro-Doppler detection on the range profile image[C]. IEEE International IGARSS, Barcelona, Spain. July, 2007: 499-502.
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出版历程
  • 收稿日期:  2009-05-06
  • 修回日期:  2009-11-23
  • 刊出日期:  2010-05-19

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