崔占忠 , 宋世和 , 徐立新 . 近炸引信原理 [M ] . 第3版. 北京 : 北京理工大学出版社 , 2009 : 76 - 100 .

CUI Z Z , SONG S H , XU L X . Principle of proximity fuze [M ] . 3rd ed. Beijing : Beijing Institute of Technology Press , 2009 : 76 - 100 . (in Chinese)

赵惠昌 . 无线电引信设计原理与方法 [M ] . 北京 : 国防工业出版社 , 2012 : 35 - 62 .

ZHAO H C . Principle and method of radio fuze design [M ] . Beijing : National Defense Industry Press , 2012 : 147 - 162 . (in Chinese)

汪仪林 , 马秋华 , 张龙山 , 等 . 引信智能化发展构想 [J ] . 探测与控制学报 , 2018 , 40 ( 3 ): 1 - 5 .

WANG Y L , MA Q H , ZHANG L S , et al . The Development visualization of fuze intell-igentize [J ] . Journal of Detection & Control , 2018 , 40 ( 3 ): 1 - 5 . (in Chinese)

汪仪林 , 张龙山 , 马秋华 . 从美军标看我国引信安全性的差距 [J ] . 探测与控制学报 , 2019 , 41 ( 3 ): 1 - 5 .

WANG Y L , ZHANG L S , MA Q H . The deficiencies of domestic fuze safety refering to U.S. millitary standards [J ] . Journal of Detection & Control , 2019 , 41 ( 3 ): 1 - 5 . (in Chinese)

AZADEGAN B , SOLERMANI H , SOLEIMANI M . Resistance against spot jamming by using pulse compression based on quadru-phase and frequency codes in radar systems [J ] . Digital Signal Processing , 2020 , 99 ( 4 ): 102679 - 102691 . DOI: 10.1016/j.dsp.2020.102679 http://doi.org/10.1016/j.dsp.2020.102679 https://linkinghub.elsevier.com/retrieve/pii/S1051200420300245 https://linkinghub.elsevier.com/retrieve/pii/S1051200420300245

代健 , 李泽 , 郝新红 , 等 . 基于目标联合特征提取的脉冲多普勒引信抗干扰方法 [J ] . 兵工学报 , 2019 , 40 ( 2 ): 225 - 233 . DOI: 10.3969/j.issn.1000-1093.2019.02.001 http://doi.org/10.3969/j.issn.1000-1093.2019.02.001 针对脉冲多普勒（PD）引信对抗信息型干扰能力不足的问题，提出一种基于目标联合特征提取的PD引信抗干扰方法。基于信息型干扰下PD引信基带滤波器的输出信号，结合PD引信目标函数，并利用二分类与单分类支持向量机构造引信期望信号空间，设计了基于目标联合特征提取和识别的PD引信原理样机。进行了抗干扰实验验证，结果表明，基于目标联合特征提取的PD引信原理样机抗干扰成功率大于90%，从而可知该方法能够显著提高PD引信抗干扰能力。

DAI J , LI Z , HAO X H , et al . Anti-jamming method for pulse doppler fuze based on joint feature extraction of target signal [J ] . Acta Armamentarii , 2019 , 40 ( 2 ): 225 - 233 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2019.02.001 http://doi.org/10.3969/j.issn.1000-1093.2019.02.001 An anti-jamming method based on the joint feature extraction of target signal for pulse Doppler (PD) fuze is proposed for the inadequate capacity of PD fuze against information type jamming. The output signal of fuze baseband filter is analyzed in consideration with the target function, and an expected target space is constructed using both two-class and one-class support vector machines (SVMs). The proposed method is verified through prototype test. The experimental results indicate that the prototype of PD fuze achieves more than 90 percent success rate in anti-jamming, which can significantly improve the anti-jamming ability of pulse Doppler fuze. Key

KIM J , LEE S , KIM Y H , et al . Classification of interference signal for automotive radar system with convolutional neural network [J ] . IEEE Access , 2020 , 8 ( 9 ): 176717 - 176727 . DOI: 10.1109/Access.6287639 http://doi.org/10.1109/Access.6287639 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

YAN Z S , HAO X H , LI R , et al . Target re-cognition technology of pulse doppler radio fuze based on bandwidth characteristics for anti-chaff jamming [C ] // Proceedings of 2019 IEEE Asia-Pacific Conference on Applied Electromagnetics . Malacca, Malaysia : IEEE , 2019 .

RAI P K , IDSOE H , YAKKATI R R , et al . Localization and activity classification of unmanned aerial vehicle using mmWave FMCW radars [J ] . IEEE Sensors Journal , 2021 , 21 ( 14 ): 16043 - 16053 . DOI: 10.1109/JSEN.2021.3075909 http://doi.org/10.1109/JSEN.2021.3075909 https://ieeexplore.ieee.org/document/9417613/ https://ieeexplore.ieee.org/document/9417613/

ZHAO S S , ZHANG L R , ZHOU Y , et al . Signal fusion based algorithms to discriminate between radar targets and deception jamming in distributed multiple radar architectures [J ] . IEEE Sensors Journal , 2015 , 15 ( 11 ): 6697 - 6706 . DOI: 10.1109/JSEN.2015.2440769 http://doi.org/10.1109/JSEN.2015.2440769 http://ieeexplore.ieee.org/document/7117343/ http://ieeexplore.ieee.org/document/7117343/

郝新红 , 杜涵宇 , 陈齐乐 . 调频引信粗糙面目标与干扰信号识别 [J ] . 北京航空航天大学学报 , 2019 , 45 ( 10 ): 1946 - 1955 .

HAO X H , DU H Y , CHEN Q L . Rough surface target and jamming signal recognition of FM fuze [J ] . Journal of Beijing University of Aeronautics and Astronautics , 2019 , 45 ( 10 ): 1946 - 1955 . (in Chinese)

刘歌 , 张国毅 , 田榛熔 . 基于时频图像三维熵特征的雷达信号识别 [J ] . 火力与指挥控制 , 2016 , 41 ( 12 ): 169 - 173 .

LIU G , ZHANG G Y , TIAN Z R . Radar signal recognition based on three dimensional entropy features of time-frequency image [J ] . Fire Control & Command Control , 2016 , 41 ( 12 ): 169 - 173 . (in Chinese)

谢平 , 杜义浩 , 黄双峰 . 基于信息熵的复杂机械系统非线性特征提取方法研究 [J ] . 振动与冲击 , 2008 , 27 ( 7 ): 135 - 137 .

XIE P , DU Y H , HUANG S F . Research on non-linear feature extracting method of complex mechanical system based on information entropy . Journal of Vibration and Shock , 2008 , 27 ( 7 ): 135 - 137 . (in Chinese)

张葛祥 , 胡来招 , 金炜东 . 基于熵特征的雷达辐射源信号识别 [J ] . 电波科学学报 , 2005 , 20 ( 4 ): 30 - 35 .

ZHANG G X , HU L Z , JIN W D . Radar emitter signal recognition based on entropy features [J ] . Chinese Journal of Radio Science , 2005 , 20 ( 4 ): 30 - 35 . (in Chinese)

GUAN X M , MA J X , ZHANG W D . Detection and classification on amateur drones based on cepstrum of radio frequency signal [J ] . Transactions of Nanjing University of Aeronautics and Astronautics , 2021 , 38 ( 4 ): 597 - 606 .

JIANG X Y , LI S . BAS: beetle antennae search algorithm for optimization problems [J ] . International Journal of Robotics and Control , 2018 , 1 ( 1 ): 2577 - 2582 .

JIANG X Y , LI S . Beetle antennae search without parameter tuning (BAS-WPT) for multiobjective optimization [J ] . Filomat , 2020 , 34 ( 15 ): 5113 - 5119 . DOI: 10.2298/FIL2015113J http://doi.org/10.2298/FIL2015113J https://doiserbia.nb.rs/Article.aspx?ID=0354-51802015113J https://doiserbia.nb.rs/Article.aspx?ID=0354-51802015113J Beetle antennae search (BAS) is an efficient meta-heuristic algorithm inspired\n by foraging behaviors of beetles. This algorithm includes several parameters\n for tuning and the existing results are limited to solve single objective\n optimization. This work pushes forward the research on BAS by providing one\n variant that releases the tuning parameters and is able to handle\n multi-objective optimization. This new approach applies normalization to\n simplify the original algorithm and uses a penalty function to exploit\n infeasible solutions with low constraint violation to solve the constraint\n optimization problem. Extensive experimental studies are carried out and the\n results reveal efficacy of the proposed approach to constraint handling.

周志华 . 机器学习 [M ] . 北京 : 清华大学出版社 , 2016 : 97 - 114 .

ZHOU Z H . Machine learning [M ] . Beijing : Tsinghua University Press , 2016 : 97 - 114 . (in Chinese)

ROTH M W . Survey of neural network technology for automatic target recognition [J ] . IEEE Transcations on Neural Networks , 1990 , 1 ( 1 ): 28 - 43 .

SCHUESSLER C , HOFFMANN VOSSIEK M . Super-resolution radar imaging with sparse arrays using a deep neural network trained with enhanced virtual data [J ] . IEEE Journal of Microwaves , 2023 , 3 ( 3 ): 980 - 993 . DOI: 10.1109/JMW.2023.3285610 http://doi.org/10.1109/JMW.2023.3285610 https://ieeexplore.ieee.org/document/10175032/ https://ieeexplore.ieee.org/document/10175032/