雷达辐射源个体识别综述

史亚; 张文博; 朱明哲; 王磊; 徐胜军

doi:10.11999/JEIT210161

雷达辐射源个体识别综述

doi: 10.11999/JEIT210161

1.
西安建筑科技大学信息与控制工程学院西安 710055
2.
西安电子科技大学电子工程学院西安 710071

基金项目: 国家自然科学基金(61803293, 61501357, 61301286, 61203137)，陕西省自然科学基础研究计划(2019JQ760)

详细信息

作者简介:
史亚：女，1985年生，博士，讲师，研究方向为机器学习、雷达辐射源识别

张文博：男，1985年生，博士，副教授，研究方向为人工智能、辐射源识别

朱明哲：男，1982年生，博士，副教授，研究方向为非平稳信号处理

王磊：男，1979年生，博士，副教授，研究方向为信号处理、机器学习、雷达对抗等

徐胜军：男，1976年生，博士，副教授，研究方向为视觉感知、人工智能与智动化系统等

通讯作者:
史亚　shiyaworld@163.com

中图分类号: TN974
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- 被引次数: 0
出版历程
- 收稿日期: 2021-02-25
- 修回日期: 2022-04-21
- 网络出版日期: 2022-04-26
- 刊出日期: 2022-06-21

Specific Radar Emitter Identification: A Comprehensive Review

1.
School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China
2.
School of Electronic Engineering, Xidian University, Xi’an 710071, China

Funds: The National Natural Science Foundation of China (61803293, 61501357, 61301286, 61203137), The Natural Science Basic Research Plan in Shaanxi Province of China (2019JQ760)

摘要

摘要: 雷达辐射源个体识别通过提取个体特征来辨识雷达个体，是电子对抗领域的热点研究方向。近年来随着深度学习的飞速发展及其在各领域的成功应用，基于深度学习的雷达辐射源个体识别成为焦点。虽然研究多年，成果丰富，但目前尚缺少关于该方向全面、细致的综述。基于此，该文从雷达辐射源个体特征机理分析、基于手工特征的识别方法、基于深度学习的识别方法以及数据集构建4个方面着手，对雷达辐射源个体识别开展系统的综述工作，并对当前现状和未来方向进行总结与展望，旨在推动雷达辐射源个体识别理论和方法研究的新发展。
- 辐射源个体识别 /
- 个体特征 /
- 机理分析 /
- 深度学习 /
- 数据集
Abstract: Specific radar emitter identification distinguishes each radar emitter based on the extracted individual features, which is crucial for electronic countermeasures. With the rapid development of deep learning, specific radar emitter identification using deep learning architecture draws great attention recently. Despite many years of research and rich achievements, there is still lack of a comprehensive review about specific radar emitter identification at present. Therefore, a systematic review is provided in this paper from four aspects: (1) the mechanism analysis of identification; (2) the handcrafted feature-based identification methods; (3) the deep learning-based identification methods; (4) and the testing datasets. Finally, the current status and the future directions are summarized, aiming at promoting the new development of specific radar emitter identification.
- Specific emitter identification /
- Individual feature /
- Mechanism analysis /
- Deep learning /
- Dataset

HTML全文

图 1 雷达辐射源个体识别系统框图

下载: 全尺寸图片幻灯片

图 2 基于深度学习的雷达辐射源识别方法示意图

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表 1 雷达辐射源信号手工特征提取方法汇总

特征域	手工特征	代表文献(年份：参考文献编号)
时域	UAMOP曲线、瞬时幅度波形、包络	2005: [39]; 2011: [36]; 2013: [21]; 2015: [42]; 2016: [41]
	UFMOP曲线、瞬时频率波形、UPMOP曲线	2004: [30]; 2005: [39]; 2012: [38]; 2013: [21]; 2015: [42]; 2016: [41]; 2020: [40]
	频率偏差曲线、频率漂移曲线	1993: [8]; 2018: [43]
频域	载频均值与方差/偏移值、频谱	2005: [14]; 2011: [6]; 2012: [20]; 2020: [48]
	功率谱密度、频域分布密度、频谱非对称特征	2011: [6]; 2016: [31]; 2017: [47]
	双谱能量幅度与频率、双谱幅度谱及其截面	2005: [14]; 2019: [49]
	双谱对角切片/对角积分/围线积分/拉东变换	2008: [34]; 2012: [20]; 2015: [51]; 2019:[50]; 2020: [52]
	双谱2维降维、双谱第1象限、循环谱(双谱)	2011: [36]; 2018: [53]; 2019: [50]; 2020: [54,55]
时频域	短时傅里叶变换、小波变换、小波包变换	2003: [29]; 2005: [14,61]; 2010: [33]; 2017: [56]; 2018: [13,57,58,60]; 2019: [59,62]
	同步压缩变换、双线性时频分布(Cohen类)	1994: [27]; 2003: [29]; 2019:[50]; 2020: [63,64]
	模糊函数	2008: [65]; 2009: [35]; 2011: [6]; 2017: [67]; 2018: [66]; 2020: [68]
	稀疏时频分析、经验模态分解	2009: [69]; 2012: [70]; 2019: [71]
	固有时间尺度分解、变分模态分解	2019: [72]; 2020: [32,73]
其他	包络瞬态特征及其相关特征	2004: [30]; 2005:[14]; 2010: [46]; 2018: [45]; 2020: [44,74]
其他	自激指数、频推系数、相空间特征、分形特征	2007: [3]; 2008: [4]; 2017: [75]

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表 2 基于深度学习的雷达辐射源个体识别方法汇总

深度模型	代表文献(年份：参考文献编号)
深度RBM网络	2016: [22]; 2018: [57]; 2019: [44]; 2020: [52,68]
深度AE网络	2017: [56]; 2018: [60]; 2020: [63]
1维卷积网络	2017: [67]; 2018: [45,86]; 2020: [48,87,88]
2维卷积网络	2018: [15,58,90]; 2020: [89,91]
混合深度网络	2019: [59]; 2020: [40]
对抗网络	2020: [54,55,93]

下载: 导出CSV

参考文献(95)

[1]	TALBOT K I, DULEY P R, and HYATT M H. Specific emitter identification and verification[J]. Technology Review Journal, 2003, 1(1): 113–133.
[2]	LIU Mingwei and DOHERTY J. Nonlinearity estimation for specific emitter identification in multipath channels[J]. IEEE Transactions on Information Forensics and Security, 2011, 6(3): 1076–1085. doi: 10.1109/TIFS.2011.2134848
[3]	CARROLL T L. A nonlinear dynamics method for signal identification[J]. Chaos, 2007, 17(2): 023109. doi: 10.1063/1.2722870
[4]	许丹. 辐射源指纹机理及识别方法研究[D]. [博士论文], 国防科学技术大学, 2008. XU Dan. Research on mechanism and methodology of specific emitter identification[D]. [Ph. D. dissertation], National University of Defense Technology, 2008.
[5]	WILEY R G. ELINT: The Interception and Analysis of Radar Signals[M]. Boston: Artech House, 2006.
[6]	王磊. 雷达辐射源个体识别的方法研究[D]. [博士论文], 西安电子科技大学, 2011. WANG Lei. On methods for specific radar emitter identification[D]. [Ph. D. dissertation], Xidian University, 2011.
[7]	DE YOUNG D, DAHLBURG J, BEVILACQUA R, et al. The U. S. naval research laboratory: Fulfilling the Roosevelts’ vision for American naval power (1923-2005)[R]. NRL/MR/1001--06-8951, 2006.
[8]	LANGLEY L E. Specific emitter identification (SEI) and classical parameter fusion technology[C]. WESCON '93, San Francisco, USA, 1993: 377–381.
[9]	刘博. 辐射源个体识别技术的发展现状及应用建议[J]. 电子信息对抗技术, 2019, 34(4): 40–43. doi: 10.3969/j.issn.1674-2230.2019.04.008 LIU Bo. Development and application suggestion on technology of specific emitter identification[J]. Electronic Information Warfare Technology, 2019, 34(4): 40–43. doi: 10.3969/j.issn.1674-2230.2019.04.008
[10]	刘刚. 雷达指纹分析的基本理论探讨[J]. 电子对抗, 2002(6): 1–6. LIU Gang. Basic discussion on radar fingerprint analysis[J]. Electronic Warfare, 2002(6): 1–6.
[11]	周一宇, 安玮, 郭福成, 等. 电子对抗原理与技术[M]. 北京: 电子工业出版社, 2014: 235. ZHOU Yiyu, AN Wei, GUO Fucheng, et al. Principles and Technologies of Electronic Warfare System[M]. Beijing: Publishing House of Electronics Industry, 2014: 235.
[12]	ZHAO Shiqiang, ZENG Deguo, WANG Wenhai, et al. Mutation grey wolf elite PSO balanced XGBoost for radar emitter individual identification based on measured signals[J]. Measurement, 2020, 159: 107777. doi: 10.1016/j.measurement.2020.107777
[13]	LIU Shaokun, YAN Xiaopeng, LI Ping, et al. Radar emitter recognition based on SIFT position and scale features[J]. IEEE Transactions on Circuits and Systems II:Express Briefs, 2018, 65(12): 2062–2066. doi: 10.1109/TCSII.2018.2819666
[14]	张国柱. 雷达辐射源识别技术研究[D]. [博士论文], 国防科学技术大学. 2005. ZHANG Guozhu. Research on emitter identification[D]. [Ph. D. dissertation], National University of Defense Technology, 2005.
[15]	QU Zhiyu, MAO Xiaojie, and DENG Zhi’an. Radar signal intra-pulse modulation recognition based on convolutional neural network[J]. IEEE Access, 2018, 6: 43874–43884. doi: 10.1109/ACCESS.2018.2864347
[16]	张葛祥. 雷达辐射源信号智能识别方法研究[D]. [博士论文], 西南交通大学, 2005. ZHANG Gexiang. Intelligent recognition methods for radar emitter signals[D]. [Ph. D. dissertation], Southwest Jiaotong University, 2005.
[17]	周志文, 黄高明, 陈海洋, 等. 雷达辐射源识别算法综述[J]. 电讯技术, 2017, 57(8): 973–980. doi: 10.3969/j.issn.1001-893x.2017.08.020 ZHOU Zhiwen, HUANG Gaoming, CHEN Haiyang, et al. An overview of radar emitter recognition algorithms[J]. Telecommunication Engineering, 2017, 57(8): 973–980. doi: 10.3969/j.issn.1001-893x.2017.08.020
[18]	姜秋喜, 潘继飞, 陈晟. 雷达辐射源识别相关技术综述[J]. 电子对抗, 2012(2): 1–6. JIANG Qiuxi, PAN Jifei, and CHEN Sheng. Overview of radar emitter identification techniques[J]. Electronic Warfare, 2012(2): 1–6.
[19]	ZHANG Ming, DIAO Ming, GAO Lipeng, et al. Neural networks for radar waveform recognition[J]. Symmetry, 2017, 9(5): 75. doi: 10.3390/sym9050075
[20]	蒋鹏. 雷达信号细微特征分析与识别[D]. [博士论文], 哈尔滨工程大学, 2012. JIANG Peng. Subtle characteristic analysis and recognition of radar signals[D]. [Ph. D. dissertation], Harbin Engineering University, 2012.
[21]	韩韬. 脉冲信号辐射源个体识别技术研究[D]. [博士论文], 国防科学技术大学, 2013. HAN Tao. Research on the techniques of specific emitter identification for pulse signals[D]. [Ph. D. dissertation], National University of Defense Technology, 2013.
[22]	周东青, 王玉冰, 王星, 等. 基于深度限制波尔兹曼机的辐射源信号识别[J]. 国防科技大学学报, 2016, 38(6): 136–141. doi: 10.11887/j.cn.201606022 ZHOU Dongqing, WANG Yubing, WANG Xing, et al. Radar emitter signal recognition based on deep restricted Boltzmann machine[J]. Journal of National University of Defense Technology, 2016, 38(6): 136–141. doi: 10.11887/j.cn.201606022
[23]	LECUN Y, BENGIO Y, and HINTON G. Deep Learning[J]. Nature, 2015, 521(7553): 436–444. doi: 10.1038/nature14539
[24]	RIYAZ S, SANKHE K, IOANNIDIS S, et al. Deep learning convolutional neural networks for radio identification[J]. IEEE Communications Magazine, 2018, 56(9): 146–152. doi: 10.1109/MCOM.2018.1800153
[25]	国强. 雷达信号分选理论研究[M]. 北京: 科学出版社, 2010. GUO Qiang. Research on the Theory of Radar Signal Sorting[M]. Beijing: Science China Press, 2010.
[26]	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
[27]	魏东升, 巫胜洪, 唐斌. 雷达信号脉内细微特征的研究[J]. 舰船科学技术, 1994(3): 23–30.
[28]	肖先赐. 电子侦察中的关键技术[J]. 电子对抗, 1991(4): 1–6.
[29]	解文斌. 脉冲信号的特征分析和辐射源识别研究[D]. [硕士论文], 国防科学技术大学, 2003. XIE Wenbin. The research of pulse signal features and emitter identification[D]. [Master dissertation], National University of Defense Technology, 2003.
[30]	KAWALEC A and OWCZAREK R. Specific emitter identification using intrapulse data[C]. IEEE 1st European Radar Conference, Amsterdam, Netherlands, 2004: 249–252.
[31]	RU Xiaohu, HUANG Zhitao, LIU Zheng, et al. Frequency-domain distribution and band-width of unintentional modulation on pulse[J]. Electronics Letters, 2016, 52(22): 1853–1855. doi: 10.1049/el.2016.0733
[32]	GOK G, ALP Y K, and ARIKAN O. A new method for specific emitter identification with results on real radar measurements[J]. IEEE Transactions on Information Forensics and Security, 2020, 15: 3335–3346. doi: 10.1109/TIFS.2020.2988558
[33]	余志斌. 基于脉内特征的雷达辐射源信号识别研究[D]. [博士论文], 西南交通大学, 2010. YU Zhibin. Study on radar emitter signal identification based on intra-pulse features[D]. [Ph. D. dissertation], Southwest Jiaotong University, 2010.
[34]	CHEN Taowei, JIN Weidong, and LI Jie. Feature extraction using surrounding-line integral bispectrum for radar emitter signal[C]. IEEE International Joint Conference on Neural Networks, Hong Kong, China, 2008: 294–298.
[35]	李林, 姬红兵. 基于模糊函数的雷达辐射源个体识别[J]. 电子与信息学报, 2009, 31(11): 2546–2551. doi: 10.3724/SP.J.1146.2008.01406 LI Lin and JI Hongbing. Specific emitter identification based on ambiguity function[J]. Journal of Electronics &Information Technology, 2009, 31(11): 2546–2551. doi: 10.3724/SP.J.1146.2008.01406
[36]	LI Lin and JI Hongbing. Radar emitter recognition based on cyclostationary signatures and sequential iterative least-square estimation[J]. Expert Systems with Applications, 2011, 38(3): 2140–2147. doi: 10.1016/j.eswa.2010.07.155
[37]	山世光, 阚美娜, 刘昕, 等. 深度学习: 多层神经网络的复兴与变革[J]. 科技导报, 2016, 34(14): 60–70. doi: 10.3981/j.issn.1000-7857.2016.14.007 SHAN Shiguang, KAN Meina, LIU Xin, et al. Deep learning: The revival and transformation of multi layer neural networks[J]. Science &Technology Review, 2016, 34(14): 60–70. doi: 10.3981/j.issn.1000-7857.2016.14.007
[38]	叶浩欢, 柳征, 姜文利. 考虑多普勒效应的脉冲无意调制特征比较[J]. 电子与信息学报, 2012, 34(11): 2654–2659. doi: 10.3724/SP.J.1146.2012.00400 YE Haohuan, LIU Zheng, and JIANG Wenli. A comparison of unintentional modulation on pulse features with the consideration of Doppler effect[J]. Journal of Electronics &Information Technology, 2012, 34(11): 2654–2659. doi: 10.3724/SP.J.1146.2012.00400
[39]	LIU Jun, LEE J P Y, LI Lingjie, et al. Online clustering algorithms for radar emitter classification[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(8): 1185–1196. doi: 10.1109/TPAMI.2005.166
[40]	秦鑫, 黄洁, 王建涛, 等. 基于无意调相特性的雷达辐射源个体识别[J]. 通信学报, 2020, 41(5): 104–111. doi: 10.11959/j.issn.1000-436x.2020084 QIN Xin, HUANG Jie, WANG Jiantao, et al. Radar emitter identification based on unintentional phase modulation on pulse characteristic[J]. Journal on Communications, 2020, 41(5): 104–111. doi: 10.11959/j.issn.1000-436x.2020084
[41]	RU Xiaohu, YE Haohuan, LIU Zheng, et al. An experimental study on secondary radar transponder UMOP characteristics[C]. The 13th European Radar Conference, London, UK, 2016: 314–317.
[42]	陈沛铂, 李纲. 应用动态时间规整算法实现雷达辐射源个体识别[J]. 信号处理, 2015, 31(8): 1035–1040. doi: 10.3969/j.issn.1003-0530.2015.08.021 CHEN Peibo and LI Gang. Applying dynamic time warping algorithm to specific radar emitter identification[J]. Journal of Signal Processing, 2015, 31(8): 1035–1040. doi: 10.3969/j.issn.1003-0530.2015.08.021
[43]	ZHAO Y, WU L, ZHANG J, et al. Specific emitter identification using geometric features of frequency drift curve[J]. Bulletin of the Polish Academy of Sciences:Technical Sciences, 2018, 66(1): 99–108. doi: 10.24425/119063
[44]	徐宇恒, 程嗣怡, 董晓璇, 等. 基于DBN特征提取的雷达辐射源个体识别[J]. 空军工程大学学报:自然科学版, 2020, 20(6): 91–96,108. doi: 10.3969/j.issn.1009-3516.2019.06.014 XU Yuheng, CHENG Siyi, DONG Xiaoxuan, et al. Radar specific emitter identification based on DBN feature extraction[J]. Journal of Air Force Engineering University:Natural Science Edition, 2020, 20(6): 91–96,108. doi: 10.3969/j.issn.1009-3516.2019.06.014
[45]	冷鹏飞, 徐朝阳. 一种深度强化学习的雷达辐射源个体识别方法[J]. 兵工学报, 2018, 39(12): 2420–2426. doi: 10.3969/j.issn.1000-1093.2018.12.016 LENG Pengfei and XU Chaoyang. Specific emitter identification based on deep reinforcement learning[J]. Acta Armamentarii, 2018, 39(12): 2420–2426. doi: 10.3969/j.issn.1000-1093.2018.12.016
[46]	王宏伟, 赵国庆, 王玉军. 基于脉冲包络前沿高阶矩特征的辐射源个体识别[J]. 现代雷达, 2010, 32(10): 42–45,49. doi: 10.3969/j.issn.1004-7859.2010.10.010 WANG Hongwei, ZHAO Guoqing, and WANG Yujun. Specific emitter identification based on higher order moment of the envelope’s front edge[J]. Modern Radar, 2010, 32(10): 42–45,49. doi: 10.3969/j.issn.1004-7859.2010.10.010
[47]	RU Xiaohu, LIU Zheng, HUANG Zhitao, et al. Evaluation of unintentional modulation for pulse compression signals based on spectrum asymmetry[J]. IET Radar, Sonar & Navigation, 2017, 11(4): 656–663. doi: 10.1049/iet-rsn.2016.0248
[48]	XIAO Yao and WEI Xizhang. Specific emitter identification of radar based on one dimensional convolution neural network[J]. Journal of Physics:Conference Series, 2020, 1550(3): 032114. doi: 10.1088/1742-6596/1550/3/032114
[49]	CAO Ru, CAO Jiuwen, MEI Jianping, et al. Radar emitter identification with bispectrum and hierarchical extreme learning machine[J]. Multimedia Tools and Applications, 2019, 78(20): 28953–28970. doi: 10.1007/s11042-018-6134-y
[50]	胡德秀, 赵拥军, 陈世文, 等. 雷达辐射源信号分析与处理[M]. 北京: 清华大学出版社, 2019. HU Dexiu, ZHAO Yongjun, CHEN Shiwen, et al. Signal Analysis and Processing of Radar Emitter[M]. Beijing: Tsinghua University Press, 2019: 165.
[51]	哈尔滨工业大学. 一种基于相位噪声无意调制特征的雷达辐射源识别方法[P]. 中国专利, 201510263140.2, 2015. Harbin Institute of Technology. Radar radiation source identification method based on phase noise unintentional modulation characteristic[P]. China Patent, 201510263140.2, 2015.
[52]	ZHOU Yipeng, WANG Xing, CHEN You, et al. Specific emitter identification via bispectrum-radon transform and hybrid deep model[J]. Mathematical Problems in Engineering, 2020, 2020: 7646527. doi: 10.1155/2020/7646527
[53]	DING Lida, WANG Shilian, WANG Fanggang, et al. Specific emitter identification via convolutional neural networks[J]. IEEE Communications Letters, 2018, 22(12): 2591–2594. doi: 10.1109/LCOMM.2018.2871465
[54]	CHEN Peibo, GUO Yulan, LI Gang, et al. Adversarial shared-private networks for specific emitter identification[J]. Electronics Letters, 2020, 56(6): 296–299. doi: 10.1049/el.2019.3207
[55]	CHEN Peibo, GUO Yulan, LI Gang, et al. Discriminative adversarial networks for specific emitter identification[J]. Electronics Letters, 2020, 56(9): 438–441. doi: 10.1049/el.2020.0116
[56]	周志文, 黄高明, 高俊, 等. 一种深度学习的雷达辐射源识别算法[J]. 西安电子科技大学学报:自然科学版, 2017, 44(3): 77–82. doi: 10.3969/j.issn.1001-2400.2017.03.014 ZHOU Zhiwen, HUANG Gaoming, GAO Jun, et al. Radar emitter identification algorithm based on deep learning[J]. Journal of Xidian University, 2017, 44(3): 77–82. doi: 10.3969/j.issn.1001-2400.2017.03.014
[57]	WANG Xuebao, HUANG Gaoming, ZHOU Zhiwen, et al. Radar emitter recognition based on the energy cumulant of short time Fourier transform and reinforced deep belief network[J]. Sensors, 2018, 18(9): 3103. doi: 10.3390/s18093103
[58]	KONG Mingxin, ZHANG Jing, LIU Weifeng, et al. Radar emitter identification based on deep convolutional neural network[C]. International Conference on Control, Automation and Information Sciences, Hangzhou, China, 2018: 309–314.
[59]	叶文强, 俞志富, 张奎. 基于DAE+CNN辐射源信号识别算法[J]. 计算机应用研究, 2019, 36(12): 3815–3818. doi: 10.19734/j.issn.1001-3695.2018.07.0409 YE Wenqiang, YU Zhifu, and ZHANG Kui. Recognition algorithm of emitter signal based on DAE+CNN[J]. Application Research of Computers, 2019, 36(12): 3815–3818. doi: 10.19734/j.issn.1001-3695.2018.07.0409
[60]	黄颖坤, 金炜东, 余志斌, 等. 基于深度学习和集成学习的辐射源信号识别[J]. 系统工程与电子技术, 2018, 40(11): 2420–2425. doi: 10.3969/j.issn.1001-506X.2018.11.05 HUANG Yingkun, JIN Weidong, YU Zhibin, et al. Radar emitter signal recognition based on deep learning and ensemble learning[J]. Systems Engineering and Electronics, 2018, 40(11): 2420–2425. doi: 10.3969/j.issn.1001-506X.2018.11.05
[61]	柳征, 姜文利, 周一宇. 基于小波包变换的辐射源信号识别[J]. 信号处理, 2005, 21(5): 460–464. LIU Zheng, JIANG Wenli, and ZHOU Yiyu. Emitter signals recognition based on wavelet packet transform[J]. Signal Processing, 2005, 21(5): 460–464.
[62]	CAO Yang, BAI Jinliang, LI Hongbo, et al. Deep representation method for radar emitter signal using wavelet packets decomposition[J]. The Journal of Engineering, 2019, 2019(19): 6282–6286. doi: 10.1049/joe.2019.0256
[63]	ZHU Mingzhe, FENG Zhenpeng, ZHOU Xianda, et al. Specific emitter identification based on synchrosqueezing transform for civil radar[J]. Electronics, 2020, 9(4): 658. doi: 10.3390/electronics9040658
[64]	SEDDIGHI Z, AHMADZADEH M R, and TABAN M R. Radar signals classification using energy-time-frequency distribution features[J]. IET Radar, Sonar & Navigation, 2020, 14(5): 707–715. doi: 10.1049/iet-rsn.2019.0331
[65]	普运伟, 金炜东, 朱明, 等. 雷达辐射源信号模糊函数主脊切面特征提取方法[J]. 红外与毫米波学报, 2008, 27(2): 133–137. doi: 10.3321/j.issn:1001-9014.2008.02.012 PU Yunwei, JIN Weidong, ZHU Ming, et al. Extracting the main ridge slice characteristics of ambiguity function for radar emitter signals[J]. Journal of Infrared and Millimeter Waves, 2008, 27(2): 133–137. doi: 10.3321/j.issn:1001-9014.2008.02.012
[66]	许程成, 周青松, 张剑云, 等. 导数约束平滑条件下基于模糊函数特征的雷达辐射源信号识别方法[J]. 电子学报, 2018, 46(7): 1663–1668. doi: 10.3969/j.issn.0372-2112.2018.07.018 XU Chengcheng, ZHOU Qingsong, ZHANG Jianyun, et al. Radar emitter recognition based on ambiguity function features with derivative constraint on smoothing[J]. Acta Electronica Sinica, 2018, 46(7): 1663–1668. doi: 10.3969/j.issn.0372-2112.2018.07.018
[67]	西北工业大学. 一种基于深度学习的雷达辐射源类别识别方法[P]. 中国专利, 201711145195.9, 2017. Northwestern Polytechnical University. Radar radiation source class identification method based on deep learning[P]. China Patent, 201711145195.9, 2017.
[68]	董鹏宇, 王红卫, 陈游, 等. 基于模糊函数主脊切片和深度置信网络的雷达辐射源信号识别[J]. 空军工程大学学报:自然科学版, 2020, 21(2): 84–90. doi: 10.3969/j.issn.1009-3516.2020.02.013 DONG Pengyu, WANG Hongwei, CHEN You, et al. A recognition method of radar emitter signals based on SVD of MRSAF and DBN[J]. Journal of Air Force Engineering University:Natural Science Edition, 2020, 21(2): 84–90. doi: 10.3969/j.issn.1009-3516.2020.02.013
[69]	朱明, 金炜东, 胡来招. 一种基于Spectrum原子的雷达辐射源信号识别方法[J]. 电子与信息学报, 2009, 31(1): 188–191. doi: 10.3724/SP.J.1146.2007.01167 ZHU Ming, JIN Weidong, and HU Laizhao. A novel method for radar emitter signals recognition based on spectrum atoms[J]. Journal of Electronics &Information Technology, 2009, 31(1): 188–191. doi: 10.3724/SP.J.1146.2007.01167
[70]	ZHU Bin and JIN Weidong. Radar emitter signal recognition based on EMD and neural network[J]. Journal of Computers, 2012, 7(6): 1413–1420. doi: 10.4304/jcp.7.6.1413-1420
[71]	ZHOU Zhiwen, ZHANG Jingke, and ZHANG Taotao. Specific emitter identification via feature extraction in Hilbert-Huang transform domain[J]. Progress in Electromagnetics Research, 2019, 82: 117–127. doi: 10.2528/PIERM19022502
[72]	LI Tianqi, ZHANG Yu, and YANG Xiaojing. An ITD-based method for individual recognition of secondary radar radiation source[C]. The 8th International Conference on Communications, Signal Processing, and Systems, Urumqi, China, 2019: 769–777.
[73]	HE Boxiang and WANG Fanggang. Cooperative specific emitter identification via multiple distorted receivers[J]. IEEE Transactions on Information Forensics and Security, 2020, 15: 3791–3806. doi: 10.1109/TIFS.2020.3001721
[74]	GUO Shanzeng and TRACEY H. Discriminant analysis for radar signal classification[J]. IEEE Transactions on Aerospace and Electronic Systems, 2020, 56(4): 3134–3148. doi: 10.1109/TAES.2020.2965787
[75]	WU Longwen, ZHAO Yaqin, WANG Zhao, et al. Specific emitter identification using fractal features based on box-counting dimension and variance dimension[C]. IEEE International Symposium on Signal Processing and Information Technology, Bilbao, Spain, 2017: 226–231.
[76]	FERNÁNDEZ-DELGADO M, CERNADAS E, BARRO S, et al. Do we need hundreds of classifiers to solve real world classification problems?[J]. The Journal of Machine Learning Research, 2014, 15(1): 3133–3181. doi: 10.5555/2627435.2697065
[77]	WILLSON G B. Radar classification using a neural network[C]. Proceedings of the SPIE 1294, Applications of Artificial Neural Networks, Orlando, USA, 1990: 200–210.
[78]	ROE A L. Artificial neural networks for ESM emitter identification-an initial study[C]. IEE Colloquium on Neural Networks for Systems: Principles and Applications, London, UK, 1991: 4/1–4/3.
[79]	GRANGER E, RUBIN M A, GROSSBERG S, et al. A What-and-Where fusion neural network for recognition and tracking of multiple radar emitters[J]. Neural Networks, 2001, 14(3): 325–344. doi: 10.1016/S0893-6080(01)00019-3
[80]	SHIEH C S and LIN C T. A vector neural network for emitter identification[J]. IEEE Transactions on Antennas and Propagation, 2002, 50(8): 1120–1127. doi: 10.1109/TAP.2002.801387
[81]	CHEN Wenbin, FU Kun, ZUO Jiawei, et al. Radar emitter classification for large data set based on weighted-xgboost[J]. IET Radar, Sonar & Navigation, 2017, 11(8): 1203–1207. doi: 10.1049/iet-rsn.2016.0632
[82]	张文博. 多类别智能分类器方法研究[D]. [博士论文], 西安电子科技大学, 2014. ZHANG Wenbo. Research on intelligent classifiers for multi-class classification[D]. [Ph. D. dissertation], Xidian University, 2014.
[83]	史亚, 姬红兵, 朱明哲, 等. 多核融合框架下的雷达辐射源个体识别[J]. 电子与信息学报, 2014, 36(10): 2484–2490. doi: 10.3724/SP.J.1146.2013.01698 SHI Ya, JI Hongbing, ZHU Mingzhe, et al. Specific radar emitter identification in multiple kernel fusion framework[J]. Journal of Electronics &Information Technology, 2014, 36(10): 2484–2490. doi: 10.3724/SP.J.1146.2013.01698
[84]	SHI Ya and JI Hongbing. Kernel canonical correlation analysis for specific radar emitter identification[J]. Electronics Letters, 2014, 50(18): 1318–1320. doi: 10.1049/el.2014.1458
[85]	贺丰收, 何友, 刘准钆, 等. 卷积神经网络在雷达自动目标识别中的研究进展[J]. 电子与信息学报, 2020, 42(1): 119–131. doi: 10.11999/JEIT180899 HE Fengshou, HE You, LIU Zhunga, et al. Research and development on applications of convolutional neural networks of radar automatic target recognition[J]. Journal of Electronics &Information Technology, 2020, 42(1): 119–131. doi: 10.11999/JEIT180899
[86]	SUN Jun, XU Guangluan, REN Wenjuan, et al. Radar emitter classification based on unidimensional convolutional neural network[J]. IET Radar, Sonar & Navigation, 2018, 12(8): 862–867. doi: 10.1049/iet-rsn.2017.0547
[87]	WU Bin, YUAN Shibo, LI Peng, et al. Radar emitter signal recognition based on one-dimensional convolutional neural network with attention mechanism[J]. Sensors, 2020, 20(21): 6350. doi: 10.3390/s20216350
[88]	高欣宇, 张文博, 姬红兵, 等. 新型雷达辐射源识别[J]. 中国图象图形学报, 2020, 25(6): 1171–1179. doi: 10.11834/jig.190375 GAO Xinyu, ZHANG Wenbo, JI Hongbing, et al. New radar emitter identification method[J]. Journal of Image and Graphics, 2020, 25(6): 1171–1179. doi: 10.11834/jig.190375
[89]	ZHU Mingzhe, FENG Zhenpeng, and ZHOU Xianda. A novel data-driven specific emitter identification feature based on machine cognition[J]. Electronics, 2020, 9(8): 1308. doi: 10.3390/electronics9081308
[90]	CAIN L, CLARK J, PAULS E, et al. Convolutional neural networks for radar emitter classification[C]. IEEE 8th Annual Computing and Communication Workshop and Conference, Las Vegas, USA, 2018: 79–83.
[91]	WANG Xuebao, HUANG Gaoming, MA Congshan, et al. Convolutional neural network applied to specific emitter identification based on pulse waveform images[J]. IET Radar, Sonar & Navigation, 2020, 14(5): 728–735. doi: 10.1049/iet-rsn.2019.0456
[92]	王坤峰, 左旺孟, 谭营, 等. 生成式对抗网络: 从生成数据到创造智能[J]. 自动化学报, 2018, 44(5): 769–774. doi: 10.16383/j.aas.2018.y000001 WANG Kunfeng, ZUO Wangmeng, TAN Ying, et al. Generative adversarial networks: From generating data to creating intelligence[J]. Acta Automatica Sinica, 2018, 44(5): 769–774. doi: 10.16383/j.aas.2018.y000001
[93]	GONG Jialiang, XU Xiaodong, and LEI Yingke. Unsupervised specific emitter identification method using radio-frequency fingerprint embedded InfoGAN[J]. IEEE Transactions on Information Forensics and Security, 2020, 15: 2898–2913. doi: 10.1109/TIFS.2020.2978620
[94]	RAS G, XIE Ning, VAN GERVEN M, et al. Explainable deep learning: A field guide for the uninitiated[J]. Journal of Artificial Intelligence Research, 2022, 73: 329–396. doi: 10.1613/jair.1.13200
[95]	LU Jiang, GONG Pinghua, YE Jieping, et al. Learning from very few samples: A survey[J]. arXiv: 2009.02653, 2020.