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基于CEEMDAN的雷达信号脉内细微特征提取法

王文哲 吴华 王经商 张强

王文哲, 吴华, 王经商, 等 . 基于CEEMDAN的雷达信号脉内细微特征提取法[J]. 北京航空航天大学学报, 2016, 42(11): 2532-2539. doi: 10.13700/j.bh.1001-5965.2016.0410
引用本文: 王文哲, 吴华, 王经商, 等 . 基于CEEMDAN的雷达信号脉内细微特征提取法[J]. 北京航空航天大学学报, 2016, 42(11): 2532-2539. doi: 10.13700/j.bh.1001-5965.2016.0410
WANG Wenzhe, WU Hua, WANG Jingshang, et al. Subtle intrapulse feature extraction based on CEEMDAN for radar signals[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(11): 2532-2539. doi: 10.13700/j.bh.1001-5965.2016.0410(in Chinese)
Citation: WANG Wenzhe, WU Hua, WANG Jingshang, et al. Subtle intrapulse feature extraction based on CEEMDAN for radar signals[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(11): 2532-2539. doi: 10.13700/j.bh.1001-5965.2016.0410(in Chinese)

基于CEEMDAN的雷达信号脉内细微特征提取法

doi: 10.13700/j.bh.1001-5965.2016.0410
基金项目: 国家自然科学基金(61379104);航空科学基金(20152096019)
详细信息
    作者简介:

    王文哲,男,硕士研究生。主要研究方向:雷达信号处理、电子对抗理论与技术。Tel.:029-84787681,E-mail:524940802@qq.com;吴华,女,硕士,副教授。主要研究方向:雷达辐射源识别、电子对抗理论与技术。Tel.:029-84787681,E-mail:15129291728@163.com

    通讯作者:

    吴华,Tel.:029-84787681,E-mail:15129291728@163.com

  • 中图分类号: TN97

Subtle intrapulse feature extraction based on CEEMDAN for radar signals

  • 摘要: 有效的信号特征提取是高精度雷达辐射源识别的基础,以脉冲描述字为代表的传统特征已无法满足复杂电磁环境的需要。本文提出一种基于自适应噪声完备集合经验模态分解(CEEMDAN)的有效雷达辐射源脉内细微特征提取算法。雷达信号由对非平稳、非线性信号尤为有效的CEEMDAN分解产生的个别分量重构,抑噪效果通过1 000次蒙特卡罗实验得到验证,同时设计基于该重构的一种脉内特征空间。本文方法与主流特征提取方法的识别精度在6部雷达辐射源产生的3 000个不同脉内调制的加噪信号样本上进行了实验对比,结果表明不同种类信号样本在本文特征空间中清晰可分,本文方法较之主流方法更加精确,尤其在0 dB信噪比(SNR)下仍保持90%以上的高精度。

     

  • [1] MONTAZER G,KHOSHNIAT H,FATHI V.Improvement of RBF neural networks using fuzzy-OSD algorithm in an online radar pulse classification system[J].Applied Soft Computing,2013,13(9):3831-3838.
    [2] JIANG H,PANG Z,TANG P,et al.Intrapulse modulation recognition based on pulse description words[C]//Proceedings of the 2013 6th International Congress on Image and Signal Processing.Piscataway,NJ:IEEE Press,2013,3:1367-1371.
    [3] MATUSZEWSKI J,PARADOWSKI L.The knowledge based approach for emitter identification[C]//Proceedings of the 12th International Conference on Microware & Radar,MIKON '98.Piscataway,NJ:IEEE Press,1998,3:810-814.
    [4] 刘海军,柳征,姜文利,等.基于联合参数建模的雷达辐射源识别方法[J].宇航学报,2011,32(1):142-149.LIU H J,LIU Z,JIANG W L,et al.A joint-parameter modeling based radar emitter identification method[J].Journal of Astronautics,2011,32(1):142-149(in Chinese).
    [5] 关一夫,张国毅.一种基于隐马尔科夫模型的雷达辐射源识别方法[J].火力与指挥控制,2015,40(10):98-103.GUAN Y F,ZHANG G Y.A radar emitter recognition algorithm based on hidden markov models[J].Fire Control & Command Control,2015,40(10):98-103(in Chinese).
    [6] XIAO W,WU H,YANG C.Support vector machine radar emitter identification algorithm based on AP clustering[C]//Proceedings of the 2013 International Conference on Quality,Reliability,Risk maintenance,and Safety Engineering (QR2MSE).Piscataway,NJ:IEEE Press,2013:2062-2064.
    [7] SINGH A,RAO K.Digital receiver-based electronic intelligence system configuration for the detection and identification of intrapulse modulated radar signals[J].Defence Science Journal,2014,64(2):152-158.
    [8] KAWALEC A,OWCZAREK R.Radar emitter recognition using intrapulse data[C]//Proceedings of the 15th International Conference on Microwaves,Radar and Wireless Communications,2004,MIKON-2004.Piscataway,NJ:IEEE Press,2004,2:435-438.
    [9] PU Y W,JIN W D,ZHU M,et al.Classification of radar emitter signal based on cascade feature extraction and hierarchical decision technique[C]//Proceedings of the 8th International Conference on Signal Processing.Piscataway,NJ:IEEE Press,2006.
    [10] ZHU B,JIN W D.Feature analysis of advanced radar emitter signals based on continuous wavelet transform[J].Applied Mechanics and Materials,2013,246-247:1125-1129.
    [11] PENG Z,TSE P,CHU F.A comparison study of improved Hilbert-Huang transform and wavelet transform:Application to fault diagnosis for rolling bearing[J].Mechanical Systems and Signal Processing,2005,19(5):974-988.
    [12] TORRES M,COLOMINAS M,SCHOLOTTHAUER G,et al.A complete ensemble empirical mode decomposition with adaptive noise[C]//Proceedings of the 2011 IEEE International Conference on Acoustics,Speech and Signal Processing.Piscataway,NJ:IEEE Press,2011:4144-4147.
    [13] HUANG N E,SHEN Z,LONG S,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[C]//Proceedings of the Royal Society of London A:Mathematical,Physical and Engineering Sciences.London:The Royal Society,1998,454(1971):903-995.
    [14] WU Z H,HUANG N E.Ensemble empirical mode decomposition:A noise-assisted data analysis method[J].Advances in Adaptive Data Analysis,2009,1(1):1-41.
    [15] HAHN S L.Hilbert transforms in signal processing[M].Norwood:Artech House on Demand,1996:1-55.
    [16] HUANG N E.Computing instantaneous frequency by normalizing Hilbert transform:US,6901353[P].2005-05-31.
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出版历程
  • 收稿日期:  2016-05-17
  • 修回日期:  2016-07-16
  • 刊出日期:  2016-11-20

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