多功能雷达脉冲列的语义编码与模型重建

刘章孟 袁硕 康仕乾

刘章孟, 袁硕, 康仕乾. 多功能雷达脉冲列的语义编码与模型重建[J]. 雷达学报, 2021, 10(4): 559–570. doi: 10.12000/JR21031
引用本文: 刘章孟, 袁硕, 康仕乾. 多功能雷达脉冲列的语义编码与模型重建[J]. 雷达学报, 2021, 10(4): 559–570. doi: 10.12000/JR21031
LIU Zhangmeng, YUAN Shuo, and KANG Shiqian. Semantic coding and model reconstruction of multifunctional radar pulse train[J]. Journal of Radars, 2021, 10(4): 559–570. doi: 10.12000/JR21031
Citation: LIU Zhangmeng, YUAN Shuo, and KANG Shiqian. Semantic coding and model reconstruction of multifunctional radar pulse train[J]. Journal of Radars, 2021, 10(4): 559–570. doi: 10.12000/JR21031

多功能雷达脉冲列的语义编码与模型重建

doi: 10.12000/JR21031
基金项目: 湖南省杰青(2020JJ2037),湖湘青年英才支持计划(2019RS2026),湖南省创新研究群体项目(2019JJ10004)
详细信息
    作者简介:

    刘章孟(1984–),男,湖北天门人,国防科技大学电子科学学院研究员。研究方向为电子侦察与对抗、电磁大数据、统计信号处理

    袁硕:袁 硕(1997–),男,山东济南人,国防科技大学电子科学学院硕士研究生。研究方向为雷达侦察数据处理

    康仕乾(1996–),男,河北衡水人,国防科技大学电子科学学院硕士研究生。研究方向为雷达侦察数据处理

    通讯作者:

    刘章孟 liuzhangmeng@nudt.edu.cn

  • 责任主编:唐斌 Corresponding Editor: TANG Bin
  • 中图分类号: TN971

Semantic Coding and Model Reconstruction of Multifunction Radar Pulse Train

Funds: Provincial Outstanding Youth project of Hunan (2020JJ2037), Huxiang Young Talents project of Hunan (2019RS2026), Provincial Innovation Research Group of Hunan (2019JJ10004)
More Information
  • 摘要: 从电子侦察数据中反演多功能雷达的工作模式,是电子侦察领域广泛关注的难点问题,也是充分挖掘电磁大数据情报效益的重要内容,对雷达型号识别、工作状态识别、行为意图推断、精确电子干扰等应用具有直接的支撑作用。该文以多功能雷达信号模型的简洁性为基本依据,参考信息理论定义了雷达脉冲列的复杂度度量规则,并遵循复杂度最小化准则对多功能雷达脉冲列进行语义编码,以提取雷达执行不同功能时的脉组结构,进一步地,基于脉冲列编码序列估计脉组之间的切换矩阵,从而重建了多功能雷达工作模型。该文设置典型的仿真实验对新方法的可行性和性能进行了验证,结果表明新方法能够借助编码理论,自动从多功能雷达侦察脉冲列中准确提取雷达脉组,并高精度重建多功能雷达工作模型,脉冲列的语义编码与模型重建过程对漏脉冲等数据噪声具有较强的适应能力。

     

  • 图  1  多功能雷达的工作模式示意图

    Figure  1.  Schematic diagram of the working mode of multifunctional radar

    图  2  多功能雷达的脉组结构

    Figure  2.  Pulse group structure of multifunctional radar

    图  3  多功能雷达脉冲列的层次化时序结构

    Figure  3.  Hierarchical temporal structure of multifunctional radar pulse train

    图  4  雷达脉冲列的层次化结构中蕴含了语义信息

    Figure  4.  Semantic information is contained in the hierarchical structure of multifunctional radar pulse train

    图  5  多功能雷达侦察脉冲列示意图

    Figure  5.  Schematic diagram of reconnaissance pulse train of multifunctional radar

    图  6  多功能雷达脉冲列编码模型寻优流程

    Figure  6.  Optimization process of the coding model of multifunctional radar pulse train

    图  7  多功能雷达脉组状态转移矩阵估计精度随脉组数目的变化情况

    Figure  7.  Estimation accuracy of the state transition matrix of multifunction radar pulse group with respect to different number of pulse groups

    图  8  多功能雷达脉组重建正确率随漏脉组率的变化情况

    Figure  8.  Probability of correct pulse group reconstruction with respect to different missing ratios of pulse groups

    表  1  脉冲列迭代编码过程中顺次输出的脉组字典集

    Table  1.   Sequentially extracted pulse group dictionary set from pulse train during iterative coding process

    迭代次数脉组字典集
    脉组 (µs)频次
    1229.98 98
    2229.98, 330.0098
    3229.98, 330.00, 430.0098
    4229.98, 330.00, 430.00
    284.98
    98
    109
    5229.98, 330.00, 430.00
    355.97, 284.98
    98
    109
    6229.98, 330.00, 430.00
    407.00, 355.97, 284.98
    98
    109
    7229.98, 330.00, 430.00
    407.00, 355.97, 284.98
    299.98
    98
    109
    93
    8229.98, 330.00, 430.00
    407.00, 355.97, 284.98
    299.98, 304.99
    98
    109
    93
    9229.98, 330.00, 430.00
    407.00, 355.97, 284.98
    299.98, 304.99, 310.01
    98
    109
    93
    下载: 导出CSV

    表  2  脉组切换次数统计结果

    Table  2.   Switching number between different pulse groups

    脉组1脉组2脉组3
    脉组1283633
    脉组2441831
    脉组3263944
    下载: 导出CSV

    表  3  漏脉组率为50%条件下的脉组提取结果

    Table  3.   Extracted pulse groups from a pulse train with 50% pulse missing

    脉组序号脉组(µs)频次
    1[230.02, 329.98, 429.98]65
    2[230.02, 329.98]52
    3[300.00, 304.93, 309.98]46
    4[300.00, 304.93]37
    5[407.03, 355.97, 284.97]41
    6[407.03, 355.97]59
    下载: 导出CSV
  • [1] RICHARDS M A, SCHEER J A, and HOLM W A. Principles of Modern Radar: Basic Principles[M]. Raleigh: SciTech Publishing, 2010: 33–36.
    [2] 张光义, 赵玉洁. 相控阵雷达技术[M]. 北京: 电子工业出版社, 2006: 1–6.

    ZHANG Guangyi and ZHAO Yujie. Phased Array Radar Technology[M]. Beijing: Publishing House of Electronics Industry, 2006: 1–6.
    [3] MELVIN W L and SCHEER J A. Principles of Modern Radar: Radar Applications[M]. Edison: SciTech Publishing, 2014: 8–14.
    [4] WILEY R G. ELINT: The Interception and Analysis of Radar Signals[M]. Norwood: Artech House, 2006: 1–5.
    [5] VISNEVSKI N, KRISHNAMURTHY V, WANG A, et al. Syntactic modeling and signal processing of multifunction radars: A stochastic context-free grammar approach[J]. Proceedings of the IEEE, 2007, 95(5): 1000–1025. doi: 10.1109/JPROC.2007.893252
    [6] VISNEVSKI N A. Syntactic modeling of multi-function radars[D]. [Ph. D. dissertation], McMaster University, 2005.
    [7] LIU Zhangmeng. Recognition of multifunction radars via hierarchically mining and exploiting pulse group patterns[J]. IEEE Transactions on Aerospace and Electronic Systems, 2020, 56(6): 4659–4672. doi: 10.1109/TAES.2020.2999163.
    [8] 方佳璐. 雷达信号工作模式识别研究[D]. [硕士论文], 浙江大学, 2017.

    FANG Jialu. Research of radar signal patter recognition[D]. [Master dissertation], Zhejiang University, 2017.
    [9] LI Yunjie, ZHU Mengtao, MA Yihao, et al. Work modes recognition and boundary identification of MFR pulse sequences with a hierarchical Seq2seq LSTM[J]. IET Radar, Sonar & Navigation, 2020, 14(9): 1343–1353. doi: 10.1049/iet-rsn.2020.0060
    [10] 欧健. 多功能雷达行为辨识与预测技术研究[D]. [博士论文], 国防科技大学, 2017.

    OU Jian. Research on behavior recognition and prediction techniques against multi-function radar[D]. [Ph. D. dissertation], National University of Defense Technology, 2017.
    [11] OU Jian, CHEN Yongguang, ZHAO Feng, et al. Research on extension of hierarchical structure for multi-function radar signals[C]. 2017 Progress in Electromagnetics Research Symposium-Spring, St. Petersburg, Russia, 2017.
    [12] 林令民. 雷达语义结构分析算法设计与应用[D]. [硕士论文], 北京邮电大学, 2017.

    LIN Lingmin. Design and application of radar semantic structure analysis algorithm[D]. [Master dissertation], Beijing University of Posts and Telecommunications, 2017.
    [13] GRÜNWALD P D. The Minimum Description Length Principle[M]. Cambridge: MIT Press, 2007: 29–35.
    [14] SAYOOD K, 贾洪峰, 译. 数据压缩导论[M]. 4版. 北京: 人民邮电出版社, 2014: 5–8, 259–279.

    SAYOOD K, JIA Hongfeng, translation. Introduction on Data Compression[M]. 4th ed. Beijing: Posts & Telecom Press, 2014: 5–8, 259–279.
    [15] 傅祖芸. 信息论—基础理论与应用[M]. 4版. 北京: 电子工业出版社, 2015: 1–8.

    FU Zuyun. Information Theory—Principles and Application[M]. 4th ed. Beijing: Publishing House of Electronics Industry, 2015: 1–8.
    [16] ROSVALL M and BERGSTROM C T. Maps of random walks on complex networks reveal community structure[J]. Proceedings of the National Academy of Sciences of the United States of America, 2008, 105(4): 1118–1123.
    [17] ROSVALL M and BERGSTROM C T. Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems[J]. PLoS One, 2011, 6(4): e18209. doi: 10.1371/journal.pone.0018209
    [18] TAN P N, STEINBACH M, KUMAR V, 范明, 范宏建, 译. 数据挖掘导论[M]. 2版. 北京: 人民邮电出版社, 2011: 27–38.

    TAN P N, STEINBACH M, KUMAR V, FAN Ming and FAN Hongjian, translation. Introduction to Data Mining[M]. 2nd ed. Beijing: Posts & Telecom Press, 2011: 27–38.
    [19] LIU Zhangmeng, KANG Shiqian, and CHAI Xianming. Automatic pulse repetition pattern reconstruction of conventional radars[J]. IET Radar, Sonar & Navigation, 2021, 15(5): 500–509. doi: 10.1049/rsn2.12053
    [20] JAEGER H. Observable operator models for discrete stochastic time series[J]. Neural Computation, 2000, 12(6): 1371–1398. doi: 10.1162/089976600300015411
    [21] JAEGER H, HAYKIN S, PRINCIPE J, SEJNOWSKI T, et al.. Learning Observable Operator Models Via the ES Algorithm[M]. New Directions in Statistical Signal Processing: From Systems to Brains. Cambridge: MIT Press, 2005.
    [22] BENGIO Y. Markovian models for sequential data[J]. Neural Computing Surveys, 1999, 2: 129–162.
    [23] RABINER L R. A tutorial on hidden Markov models and selected applications in speech recognition[J]. Proceedings of the IEEE, 1989, 77(2): 257–286. doi: 10.1109/5.18626
  • 加载中
图(8) / 表(3)
计量
  • 文章访问数:  210
  • HTML全文浏览量:  31
  • PDF下载量:  50
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-03-15
  • 修回日期:  2021-07-23
  • 网络出版日期:  2021-08-03
  • 刊出日期:  2021-08-28

目录

    /

    返回文章
    返回