利用分布式辐射源闪烁诱偏的抗反辐射方法

doi:10.12305/j.issn.1001-506X.2026.01.01

摘要/Abstract

摘要：

针对多个反辐射无人机(anti-radiation unmanned aerial vehicle, ARUAV)同时来袭时如何通过分布式辐射源协同实现有效诱偏以保护地面雷达的问题，提出一种面向双架ARUAV打击的分布式辐射源闪烁诱偏方法，旨在以大距离的分布式布站方式对辐射源进行闪烁辐射控制来影响ARUAV被动测角，进而改变其运行轨迹，最终在末端诱偏使其落点位于雷达辐射源安全半径之外。该方法首先分析信号延时控制形成脉内组合信号对ARUAV的测角诱偏原理并设计ARUAV运动模型，然后建立四维Q表深度Q学习框架，根据雷达安全距离条件建立奖励函数，以一定空域的ARUAV位置和速度作为输入，进行强化学习模型训练。仿真结果表明，所提方法诱偏距离至少为515.91 m，优于传统固定辐射诱偏方法，且较同等布站条件固定辐射的末端诱偏方法诱偏距离至少提升68.59%。

关键词: 反辐射无人机, 分布式辐射源, 强化学习, 深度Q学习

Abstract:

Addressing the issue of how to effectively decoy and protect ground radar through distributed radiation sources coordination when multiple anti-radiation unmanned aerial vehicles (ARUAV) attack simultaneously, a distributed radiation sources blinking decoy method for dual-ARUAV strikes is proposed. The aim is to control the blinking radiation of radiation sources in a distributed stationing manner at a long distance to affect the passive angle measurement of ARUAV, thereby altering its trajectory and ultimately decoying it to land outside the safe radius of the radar radiation sources at the end. This method first analyzes the principle of angle measurement deception for ARUAV using intra-pulse combined signals formed by signal delay control, and designs an ARUAV motion model. Then, a four-dimensional Q-table deep Q-learning framework is established, and a reward function is established based on radar safety distance conditions. The ARUAV position and velocity in a certain airspace are used as inputs for reinforcement learning model training. The simulation results show that the decoy distance of the proposed method is at least 515.91 m, which is better than that of the traditional fixed radiation decoy method, and the decoy distance is at least 68.59% higher than that of the terminal decoy method of fixed radiation under the same station distribution conditions.

Key words: anti-radiation unmanned aerial vehicle (ARUAV), distributed radiation source, reinforcement learning, deep Q-learning (DQL)

中图分类号:

TN 973

林志康, 刘甲磊, 马佳智, 施龙飞, 徐进宝. 利用分布式辐射源闪烁诱偏的抗反辐射方法[J]. 系统工程与电子技术, 2026, 48(1): 1-11.

Zhikang LIN, Jialei LIU, Jiazhi MA, Longfei SHI, Jinbao XU. Counter-anti-radiation method method using distributed radiation source blinking decoy[J]. Systems Engineering and Electronics, 2026, 48(1): 1-11.

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参考文献 28

1	FONTANA S, DI LAURO F. An overview of sensors for long range missile defense[J]. Sensors, 2022, 22 (24): 9871. doi: 10.3390/s22249871
2	易伟, 袁野, 刘光宏, 等. 多雷达协同探测技术研究进展: 认知跟踪与资源调度算法[J]. 雷达学报, 2023, 12 (3): 471- 499.
	YI W, YUAN Y, LIU G H, et al. Recent advances in multi-radar collaborative surveillance: cognitive tracking and resource scheduling algorithms[J]. Journal of Radars, 2023, 12 (3): 471- 499.
3	齐铖, 谢军伟, 张浩为, 等. 基于防空目标探测与跟踪的雷达资源管理技术研究综述[J]. 信号处理, 2024, 40 (11): 1972- 1989.
	QI C, XIE J W, ZHANG H W, et al. Review of radar resource management technology for air defense target detection and tracking[J]. Journal of Signal Processing, 2024, 40 (11): 1972- 1989.
4	ZOU J B, GAO K, ZHANG E Y. Research on electromagnetic scattering characteristics of anti-radiation missile[C]//Proc. of the 3rd International Conference on Communication Software and Networks, 2011: 470−473.
5	NERI F. Introduction to electronic defense systems[M]. 3 ed. Norwood: Artech House, 2018.
6	李玮, 程磊, 逯怀刚, 等. 俄乌冲突中反辐射导弹的作战运用与启示[J]. 航天电子对抗, 2023, 39 (3): 5- 9.
	LI W, CHENG L, LU H G, et al. Combat use and enlightenment for anti-radiation missile in the Russia-Ukraine conflict[J]. Aerospace Electronic Warfare, 2023, 39 (3): 5- 9.
7	周伟光, 罗积润, 贾玉贵, 等. 雷达配置诱饵对抗反辐射导弹的仿真[J]. 电子与信息学报, 2010, 32 (6): 1370- 1376.
	ZHOU W G, LUO J R, JIA Y G, et al. Simulation of radar equipped with decoys for counteracting anti-radiation missile[J]. Journal of Electronics & Information Technology, 2010, 32 (6): 1370- 1376.
8	ZOU J B, GAO K, ZHANG E Y. Using radar echo to confront anti-radiation missiles[J]. Electronics Letters, 2011, 47(5): 340−341.
9	ZOU J B, GAO K, LU S J, et al. Coherent decoys jamming anti-radiation missiles[C]//Proc. of the Jordan Conference on Applied Electrical Engineering and Computing Technologies, 2013.
10	EMADI M, JAFARGHOLI A, MOGHADAM H S, et al. New anti-ARM technique by using random phase and amplitude active decoys[J]. Progress in Electromagnetics Research, 2008, 87 (92): 297- 311.
11	DONG W F, LIU Q, CHENG Z K, et al. The deceptive effect of blinking decoys on ARMs[C]//Proc. of the Applied Informatics and Communication: International Conference, 2011: 338−347.
12	RUTKOWSKI A K, CŻYZEWSKI M, WITCZAK A, et al. Protection of radar against anti-radiation missile using single electromagnetic decoy[C]// Proc. of the 16th International Radar Symposium, 2015: 973−978.
13	汤建龙, 郭立博, 董阳阳. 基于到达时间和到达方向联合定位的机动有源诱偏方法[J]. 兵工学报, 2020, 41 (10): 2088- 2095.
	TANG J L, GUO L B, DONG Y Y. Maneuvering active decoying method based on joint TOA-DOA localization[J]. Acta Armamentarii, 2020, 41 (10): 2088- 2095.
14	YANG J, XU J H. Analysis of three-point source decoy against anti-radiation missile[C]//Proc. of the 5th International Conference on Artificial Intelligence and Pattern Recognition, 2022: 1159−1163.
15	LESICKA A, SLESICKI B. The concept of disrupting anti-radiation missiles in a radar decoy system[J]. Aviation and Security Issues, 2023, 3 (1): 167- 181. doi: 10.55676/asi.v3i1.52
16	徐宏, 尚朝轩, 韩壮志, 等. 组网火控雷达抗反辐射导弹的闪烁诱偏方法[J]. 系统工程与电子技术, 2011, 33 (5): 1146- 1150.
	XU H, SHANG C X, HAN Z Z, et al. Blinking decoying method for countering anti-radiation missiles in fire-control radar network[J]. Systems Engineering and Electronic Technology, 2011, 33 (5): 1146- 1150.
17	LAKSHMI E V, SASTRY N N, RAO B P. Optimum active decoy deployment for effective deception of missile radars[C]//Proc. of the CIE International Conference on Radar, 2011: 234−237.
18	VIJAYALAKSHMI E A. Analysis of active decoy deployment against anti-radiation missiles[J]. International Journal of Engineering & Technology, 2018, 7(4): 4814−4818.
19	MATTILA V, VIRTANEN K, MUTTILAINEN L, et al. Optimizing locations of decoys for protecting surface-based radar against anti-radiation missile with multi-objective ranking and selection[C]//Proc. of the Winter Simulation Conference, 2014: 2319−2330.
20	ŁUSZCZYK M. Wybrane problemy ochrony radarów przed rakietami antyradiolokacyjnymi[J]. Problemy Mechatroniki: Uzbrojenie, Lotnictwo, Inżynieria Bezpieczeństwa, 2014, 5 (2): 115- 122.
21	KAWALEC A, DUDCZYK J. Identification of emitter sources in the aspect of their fractal features[J]. Bulletin of the Polish Academy of Sciences-Technical Sciences, 2013, 61 (3): 623- 628. doi: 10.2478/bpasts-2013-0065
22	RUTKOWSKI A, KAWALEC A. A concept of a microwave seeker designed for ananti-radiation missile[C]//Proc. of the 12th Conference on Reconnaissance and Electronic Warfare System, 2019, 11055: 210−215.
23	KHMARSKIY P A, MUXAMMEDOV B M, JURAEV D A. Radar protection system against anti-radar missiles with integrated detection channel[J]. Advanced Engineering Days, 2023, 7, 142- 144.
24	王跃东, 顾以静, 梁彦, 等. 伴随压制干扰与组网雷达功率分配的深度博弈研究[J]. 雷达学报, 2023, 12 (3): 642- 656.
	WANG Y D, GU Y J, LIANG Y, et al. Deep game of escorting suppressive jamming and networked radar power allocation[J]. Journal of Radars, 2023, 12 (3): 642- 656.
25	解烽, 刘环宇, 胡锡坤, 等. 基于复数域深度强化学习的多干扰场景雷达抗干扰方法[J]. 雷达学报, 2023, 12 (6): 1290- 1304.
	XIE F, LIU H Y, HU X K, et al. A radar anti-jamming method under multi jamming scenarios based on deep reinforcement learning in complex domains[J]. Journal of Radars, 2023, 12 (6): 1290- 1304.
26	石荣著. 干涉仪测向原理、方法与应用[M]. 北京: 电子工业出版社, 2023.
	SHI R Z. Principle, method and application for direction finding by interferometer[M]. Beijing: Publishing House of Electronics Industry, 2023.
27	JANG B, KIM M, HARERIMANA G, et al. Q-learning algorithms: a comprehensive classification and applications[J]. IEEE Access, 2019, 7 (1): 133653- 133667.
28	林志康, 施龙飞, 刘甲磊, 等. 基于深度Q学习的组网雷达闪烁探测调度方法[J]. 系统工程与电子技术, 2025, 47 (5): 1443- 1452.
	LIN Z K, SHI L F, LIU J L, et al. Scintillation scheduling method of netted radar based on deep Q learning[J]. Systems Engineering and Electronics, 2025, 47 (5): 1443- 1452.

模式	辐射源1	辐射源2	辐射源3	辐射源4	辐射源5
1	1	1	0	0	0
2	1	0	0	1	0
3	0	1	1	0	0
4	0	1	0	0	1
5	0	0	1	1	0
6	0	0	0	1	1
7	0	0	1	1	1
8	0	1	1	0	1
9	1	0	0	1	1
10	1	0	1	1	0
11	1	1	0	0	1
12	1	1	1	0	0

模式	辐射源编号	方位角/（°）	俯仰角/（°）
—	1	42.709 4	21.586 9
—	2	42.878 9	20.122 7
延时模式1	1, 2	44.972 9	37.701 0
延时模式2	1, 2	44.429 8	24.643 8
延时模式3	1, 2	44.886 0	47.835 1

参数	数值
采样频率/MHz	150
脉宽/μs	100
载频/GHz	3
辐射源1坐标/m	[1 000, 2 000, 0]
辐射源2坐标/m	[0, 1 000, 0]
ARUAV位置点/×10³m	[14, 14, 7]

参数	数值
干涉仪短基线长度	$\lambda /2$
干涉仪长基线长度	$3\lambda /2$
采样门限	$0.8 \max (S(n))$
采样频率/MHz	150
ARUAV1发射空域/×10³ m	[13,15], [13,15],[6,8]
ARUAV2发射空域/×10³ m	[13,15],−[13,15],[6,8]
ARUAV速度/马赫	3~4

参数	数值
脉宽/μs	100
占空比/%	20, 10
载频/GHz	3
辐射源1坐标/m	[1000, 2000, 0]
辐射源2坐标/m	[0, 1000, 0]
辐射源3坐标/m	[1000, 0, 0]
辐射源4坐标/m	[0, −1000, 0]
辐射源5坐标/m	[1000, −2000, 0]