基于态势演化博弈的无人机集群动态攻防

doi:10.12305/j.issn.1001-506X.2023.08.06

Abstract

Abstract:

To solve the problem of dynamic offense and defense in unmanned aerial vehicle (UAV) swarms, a situation evolution game model is proposed. Firstly, building upon the interactions between both the base and the defender's UAV swarms, as well as the descriptions of the dynamic struggle between offender and defender, a situation evolution game model is established by taking into account situation evolution among offending and defending UAVs. Secondly, a corresponding situation evaluation function is designed to optimize individual strategy selection at each stage of combat. Then, based on this strategy selection and through the use of the social force model, the UAVs are driven to move towards designated targets, resulting in a dynamic confrontation between the offending and defending UAV swarms. Experimental results demonstrate that the dynamic movement of the UAV swarms conforms to those observed in actual air combat scenarios, verifies the superior position of a functioning base, and confirms the accuracy of the UAV swarms'adaptive decision-making through the use of the situation evolution game model.

Key words: unmanned aerial vehicle (UAV), evolutionary game, situation assessment, agent decision-making, swarm confrontation strategy

CLC Number:

V279

Lei SHENG, Manhong SHI, Yingchuan QI, Hao LI, Mingjun PANG. Dynamic offense and defense of UAV swarm based on situation evolution game[J]. Systems Engineering and Electronics, 2023, 45(8): 2332-2342.

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攻方无人机	守方无人机
攻方无人机	出击	防御
进攻	(G₁－C_i－B₁, B₁－C_j－π₁G₁)	(G₁－C_i－B₂－π₃B₃, B₂－C_j－π₁G₁+π₂R+π₃B₃)
防守	(G₂－C_i－B₁, B₁－C_j－G₂)	(G₂－C_i－B₂－π₃B₃, B₂－C_j－G₂+π₂R+π₃B₃)

序号	均衡点坐标(x, y)
1	(0, 0)
2	(1, 0)
3	(0, 1)
4	(1, 1)

均衡点序号	det(J)	tr(J)
1	－(G₁－G₂)(B₂－B₁+B₃π₃+Rπ₂)	B₁－B₂+G₁－G₂－B₃π₃－Rπ₂
2	(G₁－G₂)(B₂－B₁+B₃π₃+Rπ₂)	B₁－B₂－G₁+G₂－B₃π₃－Rπ₂
3	(G₁－G₂)(B₂－B₁+B₃π₃+Rπ₂)	B₂－B₁+G₁－G₂+B₃π₃+Rπ₂
4	－(G₁－G₂)(B₂－B₁+B₃π₃+Rπ₂)	B₂－B₁－G₁+G₂+B₃π₃+Rπ₂

博弈论模型	态势评估函数
B₂	S_ji(d_jb≤r_b)
B₁	S_ji(d_jb>r_b)
G₁	S_ib
π₁	p_i^O
G₂	S_ij
B₃	S_bj
π₃	p_b
R	S_jb
π₂	p_j^D

参数	取值
无人机速度范围/(m/s)	[60, 100]
无人机最大加速度/(m/s²)	a_max=5
无人机探测范围/m	r_s=4 000
无人机存活阈值	P_T=0.2
攻方无人机数目	N₀=10
初始条件攻方无人机采取进攻策略数目	10
初始条件攻方无人机采取防守策略数目	0
无人机携带武器数	Ω=4
无人机攻击范围/m	r_a=3 000
无人机理想杀伤概率	τ=0.6
基地探测范围/m	r_b=6 000
守方无人机数目	N_d=10
初始条件守方无人机采取防御策略数目	10
初始条件守方无人机采取出击策略数目	0

Dynamic offense and defense of UAV swarm based on situation evolution game

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变量名称	参数设定
无人机间角度优势权重比	ω₁=0.6
无人机间速度优势权重比	ω₂=0.3
无人机间距离优势权重比	ω₃=0.1
无人机与基地距离优势权重比	ω^b₂=0.7
无人机与基地角度优势权重比	ω^b₁=0.3
引力系数	k^a=1×10^－4
a	3
b	21
c	50 000
控制增益	k^q=0.4，k^w=20，k^b=40
斥力系数	k^c=3×10^－4
摩檫力系数	μ=3×10^－6

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