基于椋鸟迁徙的干扰资源动态分配方法

doi:10.12305/j.issn.1001-506X.2025.05.01

Abstract

Abstract:

Aiming at the cooperative interference resource allocation problem of unmanned aerial vehicle (UAV) cluster under the constraint of limited communication resources, a dynamic interference resource allocation method is proposed based on starling migration. In this paper, a self-organizing mechanism of UAV based on the principle of starling migration is designed. Under the condition of low information transmission, it has better real-time interference decision-making effect, which greatly alleviates the shortage of communication resources in UAV cluster. The simulation results show that under the threat scenario of radar, compared with genetic algorithm and improved ant colony algorithm, this method has 88% and 84.4% reduction of communication information respectively under the condition of ensuring the interference effect. In the high-threat scenario of radar, this method reduces the information transmission requirement by 60.75% compared with genetic algorithm and genetic-ant colony algorithm, and still has 88.75% and 85.64% interference effects.

Key words: starling migration algorithm, interference resource distribution, evaluation of interference effectiveness, cooperative interference

CLC Number:

TN974

Xiao YAN, Qingping WANG, Weidong HU, Hongyu ZHU, Chao WANG. Dynamic interference resource allocation method based on starling migration[J]. Systems Engineering and Electronics, 2025, 47(5): 1385-1394.

Figures/Tables 13

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References 33

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CFAR体制	多干扰目标下检测概率P_d
CA-CFAR	$P_{d_n}^k=\left(1+\frac{T_{\mathrm{CA}}}{1+S_n^k}\right)^{J-C}\left(1+\frac{T_{\mathrm{CA}}\left(1+I_n^k\right)}{1+S_n^k}\right)^{-J}$
GO-CFAR	$\lim\limits_{I_n^k \rightarrow \infty} P_{d_n}^k\left(S_n^k, I_n^k\right)=\left[1+\left(\frac{I_n^k}{S_n^k}\right) T_{\mathrm{GO}}\right]^{-1}$
SO-CFAR	$\lim\limits_{I_n^k \rightarrow \infty} P_{d_n}^k\left(S_n^k, I_n^k\right)=\left(1+\frac{T_{\mathrm{SO}}}{1+S}\right)^{-\frac{N}{2}}$
OS-CFAR	$P_{d_n}^k=H C_{\alpha-J}^{\mathrm{H}-J} \cdot \frac{\varGamma\left(\alpha-H+1+T_{\mathrm{OS}} \frac{1+I_n^k}{1+S_n^k}\right) \varGamma(H)}{\varGamma\left(\alpha+T_{\mathrm{OS}} \frac{1+I_n^k}{1+S_n^k}+1\right)}$

融合规则	检测概率
AND规则	$P_{d_{\text {net }}}^k=\prod\limits_{n=1}^N P_{d_n}^k$
秩K规则	$P_{d_{\text {net }}}^k=\sum\limits_{\boldsymbol{D}}\left[R(\boldsymbol{D}) \prod\limits_{S_0}\left(1-P_{d_n}^k\right) \prod\limits_{S_1} P_{d_n}^k\right]$
OR规则	$P_{d_{\mathrm{net}}}^k=1-\prod\limits_{n=1}^N\left(1-P_{d_n}^k\right)$

干扰样式	脉冲压缩增益	参数说明
随机移频干扰	$\left(1-\frac{\|\zeta\|}{B}\right)^2 B T$	ζ为移频宽度
卷积灵巧噪声干扰	$\frac{L+T}{L+1 / B}$	L为噪声时宽
间歇采样直接转发干扰	$\eta^2+2 \frac{\sin ^2(\pi \eta)}{\pi^2} B T$	η为间歇采样占空比

雷达编号	工作模式	位置信息/km	发射功率/kW
R₁ R₂ R₃	跟踪搜索搜索	(200, 200, 0) (185, 200, 0) (200, 185, 0)	150 150 150

干扰载荷序号	干扰频段范围/GHz	干扰样式	最大干扰功率/W	干扰载荷数量
1 2 3 4 5	(1.0, 4.0) (2.0, 10.0) (8.0, 12.0) (12.0, 18.0) (8.0, 18.0)	1, 2, 3 1, 2, 3 1, 2, 3 1, 2, 3 1, 2, 3	100 100 100 100 100	4 4 4 4 4

Dynamic interference resource allocation method based on starling migration

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