辐射源指纹特征提取方法述评

孙丽婷 黄知涛 王翔 王丰华 李保国

孙丽婷, 黄知涛, 王翔, 等. 辐射源指纹特征提取方法述评[J]. 雷达学报, 2020, 9(6): 1014–1031. doi: 10.12000/JR19115
引用本文: 孙丽婷, 黄知涛, 王翔, 等. 辐射源指纹特征提取方法述评[J]. 雷达学报, 2020, 9(6): 1014–1031. doi: 10.12000/JR19115
SUN Liting, HUANG Zhitao, WANG Xiang, et al. Overview of radio frequency fingerprint extraction in specific emitter identification[J]. Journal of Radars, 2020, 9(6): 1014–1031. doi: 10.12000/JR19115
Citation: SUN Liting, HUANG Zhitao, WANG Xiang, et al. Overview of radio frequency fingerprint extraction in specific emitter identification[J]. Journal of Radars, 2020, 9(6): 1014–1031. doi: 10.12000/JR19115

辐射源指纹特征提取方法述评

doi: 10.12000/JR19115
基金项目: 湖南省创新群体研究项目(2019JJ10004)
详细信息
    作者简介:

    孙丽婷(1994–) 女,山东人,博士研究生,主要研究方向为通信辐射源个体识别。E-mail: slt2009@yeah.net

    黄知涛(1976–),男,湖北人,教授,博士生导师,主要研究方向为航天电子侦察、雷达/通信信号处理、综合电子战系统与技术等。E-mail: huangzhitao@nudt.edu.cn

    王翔:王 翔(1985–),男,福建人,讲师,主要研究方向为航天电子侦察、信号处理、模式识别等。E-mail: christopherwx@163.com

    王丰华(1981–),男,山东人,讲师,主要研究方向为信号处理、模式识别等。E-mail: wfh.abc@163.com

    李保国(1977–),男,湖北人,副教授,主要研究方向为通信信号处理等。E-mail: laglbg322@163.com

    通讯作者:

    黄知涛 huangzhitao@nudt.edu.cn

    王翔 christopherwx@163.com

  • 责任主编:黄高明 Corresponding Editor: HUANG Gaoming
  • 中图分类号: TN97

Overview of Radio Frequency Fingerprint Extraction in Specific Emitter Identification (in English)

Funds: The Program for Innovative Research Groups of the Hunan Provincial Natural Science Foundation of China (2019JJ10004)
More Information
  • 摘要: 辐射源个体识别是一种仅通过信号的外部特征测量手段,提取辐射源指纹特征,从而识别发射给定信号的特定辐射源个体的技术。近年来,辐射源个体识别技术相关理论与实践应用不断完善,指纹特征提取方法的研究取得了较大的进展。该文在分析国内外大量学术研究成果的基础上,从指纹特征的内在逻辑出发提出了一种新的特征框架。该框架根据不同特征对辐射源指纹的描述特性以及相互之间的关联,将指纹特征划分为直接测量特征和降维变换特征两大类共3个层次,并系统性地梳理了辐射源指纹特征提取方法的研究现状。最后,该文对辐射源指纹特征提取的几个潜在研究方向进行了分析和展望, 希望对辐射源个体识别的研究和应用有所裨益。

     

  • 图  1  辐射源个体识别经典系统结构图[1]

    Figure  1.  Structural diagram of typical system for specific emitter identification[1]

    图  2  雷达脉冲包络

    Figure  2.  Radar pulse envelope

    图  3  4架民航飞机2次应答信号瞬时相位

    Figure  3.  Instantaneous phase characteristics of the secondary response signals of four civil aviation aircrafts

    图  4  两部FM电台信号双谱特征图

    Figure  4.  Bispectrum characteristic images of two FM radio signal

    图  5  IEEE802.11b协议的导头格式

    Figure  5.  Preamble format of standard IEEE802.11b

    图  6  经验模态分解结果示意图

    Figure  6.  Schematic of empirical mode decomposition results

    图  7  主曲线提取数据骨架

    Figure  7.  Data skeleton extracted by principal curve

    图  8  不同路径积分双谱

    Figure  8.  Integral paths of bispectrum

    图  1  Structural diagram of typical system for specific emitter identification[1]

    图  2  Radar pulse envelope

    图  3  Instantaneous phase characteristics of the secondary response signals of four civil aviation aircrafts

    图  4  Bispectrum characteristic images of two FM radio signal

    图  5  Preamble format of standard IEEE802.11b

    图  6  Schematic of empirical mode decomposition results

    图  7  Data skeleton extracted by principal curve

    图  8  Integral paths of bispectrum

    表  1  基于指纹分析内在逻辑的指纹特征分类框架下的直接测量特征

    Table  1.   Direct measurement features under the feature framework based on the inherent logic of fingerprint feature extraction

    特征方法 相关文献
    基本参数信息 常规参数 文献[1,11,12]
    包络特性 文献[1318]
    瞬时特性 文献[1923]
    调制参数 文献[2426]
    频谱分布 文献[327]
    基本变换信息 时频谱 文献[2832]
    高阶谱 文献[3337]
    循环谱 文献[38,39]
    Hilbert谱 文献[4043]
    信号特殊结构 信号导头 文献[23,44,45]
    雷达信号分析 文献[46-51]
    分解重构信息 经验模态分解 文献[42,43,5255]
    固有时间尺度分解 文献[5663]
    变分模态分解 文献[9,43,64,65]
    相空间重构 文献[2,6669]
    信号分割重构 文献[7071]
    发射机硬件特性 等效电路 文献[72]
    非线性电路 文献[73]
    频率源 文献[74]
    下载: 导出CSV

    表  2  基于指纹分析内在逻辑的指纹特征分类框架下的降维变换特征

    Table  2.   Dimensionality reduction feature under feature framework based on the inherent logic of fingerprint feature extraction

    特征方法 相关文献
    波形骨架 文献[7578]
    分形维数、复杂度 文献[42,79,80]
    特定路径积分切片 文献[38,39,81]
    熵值计算 文献[59,65,8284]
    奇异值分解等 文献[36,38,85]
    传统降维特征 文献[3,8688]
    下载: 导出CSV

    表  1  Direct measurement features under the feature framework based on the inherent logic of fingerprint feature extraction

    Feature method Reference
    Basic parameter information General parameter [1,11,12]
    Envelope feature [13-18]
    Instantaneous feature [19-23]
    Modulation parameter [24-26]
    Spectrum feature [3-27]
    Basic transformation
    information
    Time-frequency analysis [28-32]
    High-order spectrum [33-37]
    Cyclic spectrum [38,39]
    Hilbert spectrum [40-43]
    Signal special structure
    Signal preamble [23,44,45]
    Radar signal analysis [46-51]
    Decomposition and
    reconstruction information
    EMD [42,43,52-55]
    ITD [56-63]
    VMD [9,43,64,65]
    Phase space analysis [2,66-69]
    Segmentation reconstruction [70,71]
    Transmitter hardware characteristics Equivalent circuit model [72]
    Nonlinear circuit model [73]
    Frequency source circuit [74]
    下载: 导出CSV

    表  2  Dimensionality reduction feature under feature framework based on the inherent logic of fingerprint feature extraction

    Feature Method Reference
    Waveform skeleton [75-78]
    Fractal and complexity [42,79,80]
    Specific path integration/slicing [38,39,81]
    Entropy [59,65,82-84]
    SVD [36,38,85]
    Traditional dimensionality reduction [3,86-88]
    下载: 导出CSV
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  • 收稿日期:  2019-12-19
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