基于改进离散模拟退火遗传算法的雷达网协同干扰资源分配模型

doi:10.12305/j.issn.1001-506X.2024.03.07

Abstract

Abstract:

An improved discrete simulated annealing genetic algorithm (IDSA-GA) with random keys is proposed to optimize the resource allocation process in the context of distributed jammers covering target penetration radar networks. An interference effect evaluation function based on the fusion detection probability of radar networks is constructed, and IDSA-GA is used to optimize and solve the function. IDSA-GA introduces random keys on the basis of simulated annealing genetic algorithm (SA-GA) to discretize the algorithm. And during the iteration process, memory function is added to overcome the phenomenon of premature convergence. The simulation results show that compared with GA, the proposed IDSA-GA converges quickly and has strong optimization ability, which can effectively solve the problem of optimizing interference resource allocation.

Key words: radar network, cooperative jamming, resource allocation, simulated annealing genetic algorithm (SA-GA), random keys

CLC Number:

TN97

Zekun YAO, Chao WANG, Qingzhan SHI, Shaoqing ZHANG, Naichang YUAN. Cooperative jamming resource allocation model for radar network based on improved discrete simulated annealing genetic algorithm[J]. Systems Engineering and Electronics, 2024, 46(3): 824-830.

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References 19

1	张养瑞. 对雷达网的多机伴随式协同干扰技术研究[D]. 北京: 北京理工大学, 2015.
	ZHANG Y R. Research on key technologiesof cooperative ECM in multi-syndrome jammers for countering radar net[D]. Beijing: Beijing Institute of Technology, 2015.
2	赵忠凯, 王鸿. 组网雷达协同干扰资源分配模型及算法[J]. 火力与指挥控制, 2019, 44 (5): 85- 89.
	ZHAO Z K , WANG H . Model and algorithm of cooperative jamming resource allocation for network radar[J]. Fire Control and Command Control, 2019, 44 (5): 85- 89.
3	陆青, 陈荣. 实用干扰资源智能管理和控制技术[J]. 舰船科学技术, 1998, (5): 47-50, 65.
	LU Q , CHEN R . Practical interference resource intelligent management and control technology[J]. Ship Science and Technology, 1998, (5): 47-50, 65.
4	吕永胜, 王树宗, 王向伟, 等. 基于贴近度的雷达干扰资源分配策略研究[J]. 系统工程与电子技术, 2005, 27 (11): 1893-1894, 1974.
	LYU Y S , WANG S Z , WANG X W , et al. Study on the allocation tactics for radar jamming resources based on close degree[J]. Systems Engineering and Electronics, 2005, 27 (11): 1893-1894, 1974.
5	李东生, 高杨, 雍爱霞. 基于改进离散布谷鸟算法的干扰资源算法分配研究[J]. 电子与信息学报, 2016, 38 (4): 899- 905.
	LI D S , GAO Y , YONG A X . Jamming resource allocation via improved discrete cuckoo search algorithm[J]. Journal of Electronics Information Technology, 2016, 38 (4): 899- 905.
6	刘以安, 倪天权, 张秀辉, 等. 模拟退火算法在雷达干扰资源优化分配中的应用[J]. 系统工程与电子技术, 2009, 31 (8): 1914- 1917.
	LIU Y A , NI T Q , ZHANG X H , et al. Application of simulated annealing algorith-min optimizing allocation of radar jammingresources[J]. Systems Engineering and Electronics, 2009, 31 (8): 1914- 1917.
7	张养瑞, 李云杰, 高梅国. 协同干扰资源优化分配模型及算法[J]. 系统工程与电子技术, 2014, 36 (9): 1744- 1749.
	ZHANG Y R , LI Y J , GAO M G . Optimal assignment model and solution of cooperati-ve jamming resources[J]. Systems Engineering and Electronics, 2014, 36 (9): 1744- 1749.
8	柳向, 李东生, 吴世俊. 改进布谷鸟算法在协同干扰资源分配中的应用[J]. 现代雷达, 2019, 41 (2): 84- 90.
	LIU X , LI D S , WU S J . Improved cuckoo search algorithm in optimization assignment for cooperative jamming resources[J]. Modern Radar, 2019, 41 (2): 84- 90.
9	张养瑞, 高梅国, 罗皓月, 等. 基于检测概率的雷达网协同干扰效果评估方法[J]. 系统工程与电子技术, 2015, 37 (8): 1778- 1786.
	ZHANG Y R , GAO M G , LUO H Y , et al. Evaluation method of cooperative jam-ming effect on radar net based on detection probability[J]. Systems Engineering and Electronics, 2015, 37 (8): 1778- 1786.
10	汲清波, 杨帅. 基于自适应目标函数的协同干扰策略分配[J]. 应用科技, 2019, 46 (4): 70-76, 81.
	JI Q B , YANG S . Cooperative interference strategy allocation based on adaptive objective function[J]. The Application of Science and Technology, 2019, 46 (4): 70-76, 81.
11	刘忠. 基于DRFM的线性调频脉冲压缩雷达干扰新技术[D]. 长活: 国防科学技术大学, 2006.
	LIU Z. Jamming technique for countering LFM pulse compression radar based on digital radio frequency memory[D]. Changsha: National University of Defense Technology, 2006.
12	吕波, 冯起, 袁乃昌. 对LFM脉压雷达的移频压制干扰技术研究[J]. 现代雷达, 2009, 31 (1): 9-12, 17.
	LYU B , FNEG Q , YUAN N C . A study on frequency-shiftig blanket jamming to LFM pulse compression radar[J]. Modern Radar, 2009, 31 (1): 9-12, 17.
13	张煜, 杨绍全. 对线性调频雷达的卷积干扰技术[J]. 电子与信息学报, 2007, 29 (6): 1408- 1411.
	ZHANG Y , YANG S Q . Convolution jamming technique countering LFM radar[J]. Journal of Electronics Information Technology, 2007, 29 (6): 1408- 1411.
14	王雪松, 刘建成, 张文明, 等. 间歇采样转发干扰的数学原理[J]. 中国科学E辑: 信息科学, 2006, 36 (8): 891- 901.
	WANG X S , LIU J C , ZHANG W M , et al. Mathematical principle of intermittent sampling and forwarding interference[J]. Science in China Series E: Information Science, 2006, 36 (8): 891- 901.
15	何友, 关键, 孟祥伟. 雷达目标检测与恒虚警处理[M]. 北京: 清华大学出版社, 2011: 39- 40.
	HE Y , GUAN J , MENG X W . Radar target detection and constant false alarm processing[M]. Beijing: Tsinghua University Press, 2011: 39- 40.
16	WEISS M . Analysis of some modified cellaveraging CFAR processors in multiple-target situations[J]. IEEE Trans.on Aerospace and Electronic Systems, 1982, (AES-18) (1): 102- 114.
17	BEAN J C . Genetic algorithms and random keys for sequencing and optimization[J]. ORSA Journal on Computing, 1994, 6 (2): 154- 160. doi: 10.1287/ijoc.6.2.154
18	王雪梅, 王义和. 模拟退火算法与遗传算法的结合[J]. 计算机学报, 1997, 20 (4): 381- 384.
	WANG X M , WANG Y H . The combination of simulated annealing algorithm and genetic algorithm[J]. Chinese Journal of Computers, 1997, 20 (4): 381- 384.
19	冯冬青, 王非, 马雁. 遗传算法中选择交叉策略的改进[J]. 计算机工程, 2008, 34 (19): 189- 191.
	FENG D Q , WANG F , MA Y . Improvement of selection and crossover strategy in genetic algorithm[J]. Computer Engineering, 2008, 34 (19): 189- 191.

干扰样式	脉冲压缩增益	参数说明
随机移频干扰	$ \left(1-\frac{\|\zeta\|}{B}\right)^2 B \tau$	ζ为移频宽度 B为信号带宽 τ为信号时宽
卷积灵巧噪声干扰	$ \frac{\tau+\tau_n}{1 / B+\tau_n}$	τ_n为噪声时宽
间歇采样重复转发干扰	$ \left(\eta^2+2 \frac{\sin ^2({\rm{ \mathsf{ π} }} \eta)}{{\rm{ \mathsf{ π} }}^2}\right) B \tau$	η为间歇采样占空比, 取值0.5

恒虚警体制	多干扰目标下检测概率P_d
CA-CFAR	$ P_d=\left(1+\frac{T_{\mathrm{CA}}}{1+S}\right)^{J-N}\left(1+\frac{T_{\mathrm{CA}}(1+I)}{1+S}\right)^{-J}$
GO-CFAR	$ \begin{gathered} \lim P_d(S, I)=\left[1+(I / S) T_{\mathrm{GO}}\right]^{-1} \\ I \rightarrow \infty \end{gathered}$
SO-CFAR	$ \begin{gathered} \lim P_d(S, I)=\left[1+T_{\mathrm{so}}\left(P_{\mathrm{fa}}, N\right)\right]^{-N / 2} \\ I \rightarrow \infty \end{gathered}$
OS-CFAR	$ \begin{gathered} P_d=k C_{N-J}^k \cdot \\ \frac{{\mathit{\Gamma}}\left[N-k+1+T_{\mathrm{OS}}(1+I) /(1+S)\right] {\mathit{\Gamma}}(k)}{{\mathit{\Gamma}}\left(N+T_{\mathrm{OS}}(1+I) /(1+S)+1\right)} \end{gathered}$

融合规则	检测概率
AND规则	$ P_d=\prod\limits_{m=1}^M P_{d m}$
秩K规则	$ P_d=\sum\limits_{m=K}^M \sum\limits_{i=1}^{c_M^m} \prod\limits_{S_0}\left(1-P_{d m}\right) \prod\limits_{S_1} P_{d m}$
OR规则	$ P_d=1-\prod\limits_{m=1}^M\left(1-P_{d m}\right)$

编码说明	干扰机编号
编码说明	1	2	3	4	5
编码样例	1.21	2.34	2.96	3.74	1.09
对应雷达	2	3	5	4	1
干扰样式	1	2	2	3	1

作战编队	位置坐标/km
掩护目标	(-18.2, 15.1, 20.0)
干扰机1	(-17.5, 13.9, 18.9)
干扰机2	(-19.2, 13.5, 18.9)
干扰机3	(-18.1, 17.1, 19.9)
干扰机4	(-20, -15.9, 19.4)
干扰机5	(-16.1, 15.1, 19.4)

Cooperative jamming resource allocation model for radar network based on improved discrete simulated annealing genetic algorithm

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雷达目标	位置坐标/km	CFAR检测器种类	接收机带宽/MHz
雷达1	(5, 0, 0)	CA-CFAR	20
雷达2	(-6, 10.2, 0)	GO-CFAR	10
雷达3	(1.2, 6.4, 0)	SO-CFAR	7
雷达4	(0.8, -8.9, 0)	OS-CFAR	5
雷达5	(-8, 15, 0)	CA-CFAR	8

参数名称	参数值	参数名称	参数值
雷达功率/kW	150	脉冲宽度/μs	10
天线增益/dB	40	噪声系数/dB	3
目标雷达散射截面/m²	5	虚警概率	10^－6
有效噪声温度/K	290	大气及馈线损耗/dB	6

参数	干扰机编号					融合检测概率
参数	J₁	J₂	J₃	J₄	J₅	融合检测概率
雷达编号	R₃	R₂	R₁	R₅	R₄	0.126 727
干扰样式	间歇转发干扰	移频干扰	移频干扰	移频干扰	卷积灵巧噪声	0.126 727

算法	指标
算法	检测概率最优解	检测概率平均收敛值	平均收敛误差	平均迭代次数	收敛概率/%
SA-GA	0.126 727	0.126 799	0.000 072	46	90
自适应GA	0.126 727	0.127 403	0.000 676	57	30
IDSA-GA	0.126 727	0.126 727	0	21	100

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