LPI雷达信号调制识别及参数估计研究进展

doi:10.12305/j.issn.1001-506X.2024.06.09

系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (6): 1908-1924.doi: 10.12305/j.issn.1001-506X.2024.06.09

• 传感器与信号处理 • 上一篇

LPI雷达信号调制识别及参数估计研究进展

王海英¹^,²^,³, 张群英¹^,²^,*, 成文海¹^,²^,³, 董家铭¹^,²^,³, 刘小军¹^,²

1. 中国科学院空天信息创新研究院, 北京 100090
2. 电磁辐射与探测技术院重点实验室, 北京 100090
3. 中国科学院大学电子电气与通信工程学院, 北京 100049

收稿日期:2022-12-19 出版日期:2024-05-25 发布日期:2024-06-04
通讯作者: 张群英
作者简介:王海英 (1999—), 女, 博士研究生, 主要研究方向为雷达目标识别与对抗、雷达信号参数估计等
张群英 (1972—), 女, 研究员, 博士, 主要研究方向为雷达对抗技术及超宽带雷达成像
成文海 (1996—), 男, 博士研究生, 主要研究方向为雷达侦察信号处理
董家铭 (1996—), 男, 博士研究生, 主要研究方向为合成孔径雷达信号处理及电子对抗
刘小军 (1972—), 男, 研究员, 博士, 主要研究方向为超宽带雷达系统设计、超宽带雷达信号与信息处理

Research progress on LPI radar signal modulation recognition and parameter estimation

Haiying WANG¹^,²^,³, Qunying ZHANG¹^,²^,*, Wenhai CHENG¹^,²^,³, Jiaming DONG¹^,²^,³, Xiaojun LIU¹^,²

1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100090, China
2. Key Laboratory of Electromagnetic Radiation and Sensing Technology, Beijing 100090, China
3. School of Electronic Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2022-12-19 Online:2024-05-25 Published:2024-06-04
Contact: Qunying ZHANG

摘要/Abstract

摘要：

低截获概率(low probability of intercept, LPI)雷达已成为新时代雷达装备中关键的技术体制或工作模式，针对LPI雷达信号调制识别及参数估计方法的研究是当前雷达对抗侦察领域的热点。首先, 分析了几种典型LPI雷达信号的脉内特征，梳理了LPI雷达信号调制识别及参数估计的传统和主流方法，并说明其原理、优缺点和研究现状。最后，总结了现有LPI雷达信号调制识别及参数估计方法尚存的问题，并指出其未来发展趋势，旨在为今后的研究提供参考。

关键词: 雷达对抗侦察, 低截获概率雷达信号, 脉内特征, 调制识别, 参数估计

Abstract:

Low probability of intercept (LPI) radar has become a key technology system or working mode of radar equipment in the new era. The study of LPI radar signal modulation recognition and parameter estimation methods has become a hot spot in the field of radar counter reconnaissance. This paper firstly analyzes the intra-pulse characteristics of several typical LPI radar signals, sorts out the traditional and mainstream methods of LPI radar signal modulation recognition and parameter estimation, and explains their principles, advantages, disadvantages and research status. Finally, the remaining problems of existing LPI radar signal modulation recognition and parameter estimation methods are summarized, and their future development trends are also pointed out, aiming to provide some reference for future scholars' research.

Key words: radar counter reconnaissance, low probability of intercept (LPI) radar signal, intra-pulse characteristic, modulation recognition, parameter estimation

中图分类号:

TN971

王海英, 张群英, 成文海, 董家铭, 刘小军. LPI雷达信号调制识别及参数估计研究进展[J]. 系统工程与电子技术, 2024, 46(6): 1908-1924.

Haiying WANG, Qunying ZHANG, Wenhai CHENG, Jiaming DONG, Xiaojun LIU. Research progress on LPI radar signal modulation recognition and parameter estimation[J]. Systems Engineering and Electronics, 2024, 46(6): 1908-1924.

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文献	年份	神经网络输入	神经网络类型	可识别信号种类数量	SNR/dB	总体识别率/%
文献[42]	2018	CWD时频图	卷积神经网络(convolutional neural networks, CNN)	12	-6	93.58
文献[43]	2019	CWD时频图	单步多框检测器	12	-4	95.00
文献[44]	2020	CWD时频图	CNN+迁移学习	12	-6	99.00
文献[45]	2021	CWD时频图	去噪CNN	8	-10	90.00
文献[46]	2021	CWD时频图	CNN	13	0	98.60
文献[47]	2021	SPWVD时频图	密集积累网络	13	0	98.20
文献[48]	2021	CWD时频图	深度残差网络	7	-6	96.00
文献[49]	2022	CWD时频图	CNN+Swin transformer	6	-18	94.26
文献[50]	2022	WVD时频图+FSST时频图	残差网络+混洗网络	18	10	98.08
文献[51]	2022	低、中、高分辨率的STFT时频图	残差网络	16	-6	96.00
文献[52]	2022	离散傅里叶变换谱图	CNN+双向长短期记忆网络	12	-4	94.27
文献[53]	2022	CWD时频图	混洗网络	12	-2	99.36
文献[54]	2022	信号的平滑伪WVD(smoothed pseudo WVD, SPWVD)时频图	CNN+即插即用注意力模块	13	-4	99.20
文献[55]	2022	SPWVD时频图	特征压缩与激发残差网络	8	-8	93.20
文献[56]	2022	SPWVD时频图	带抗噪声损失函数的CNN	12	-10	91.17
文献[57]	2023	CWD时频图	非对称扩张卷积坐标注意力残差网络	12	-8	97.94
文献[58]	2023	WVD+WT+CWD+自适应特征	CNN	6	-13	93.00

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LPI雷达信号调制识别及参数估计研究进展

Research progress on LPI radar signal modulation recognition and parameter estimation

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