TY - JOUR
T1 - Weapon-target assignment for unmanned aerial vehicles
T2 - A multi-strategy threshold public goods game approach
AU - Bi, Wenhao
AU - Wang, Zhaoxi
AU - Xu, Yang
AU - Zhang, An
N1 - Publisher Copyright:
© 2025 China Ordnance Society
PY - 2025/6
Y1 - 2025/6
N2 - As a crucial process in the coordinated strikes of unmanned aerial vehicles (UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UAVs. Existing weapon-target assignment methods primarily focus on macro cluster constraints while neglecting individual strategy updates. This paper proposes a novel weapon-target assignment method for UAVs based on the multi-strategy threshold public goods game (PGG). By analyzing the concept mapping between weapon-target assignment for UAVs and multi-strategy threshold PGG, a weapon-target assignment model for UAVs based on the multi-strategy threshold PGG is established, which is adaptively complemented by the diverse cooperation-defection strategy library and the utility function based on the threshold mechanism. Additionally, a multi-chain Markov is formulated to quantitatively describe the stochastic evolutionary dynamics, whose evolutionary stable distribution is theoretically derived through the development of a strategy update rule based on preference-based aspiration dynamic. Numerical simulation results validate the feasibility and effectiveness of the proposed method, and the impacts of selection intensity, preference degree and threshold on the evolutionary stable distribution are analyzed. Comparative simulations show that the proposed method outperforms GWO, DE, and NSGA-II, achieving 17.18% higher expected utility than NSGA-II and reducing evolutionary stable times by 25% in large-scale scenario.
AB - As a crucial process in the coordinated strikes of unmanned aerial vehicles (UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UAVs. Existing weapon-target assignment methods primarily focus on macro cluster constraints while neglecting individual strategy updates. This paper proposes a novel weapon-target assignment method for UAVs based on the multi-strategy threshold public goods game (PGG). By analyzing the concept mapping between weapon-target assignment for UAVs and multi-strategy threshold PGG, a weapon-target assignment model for UAVs based on the multi-strategy threshold PGG is established, which is adaptively complemented by the diverse cooperation-defection strategy library and the utility function based on the threshold mechanism. Additionally, a multi-chain Markov is formulated to quantitatively describe the stochastic evolutionary dynamics, whose evolutionary stable distribution is theoretically derived through the development of a strategy update rule based on preference-based aspiration dynamic. Numerical simulation results validate the feasibility and effectiveness of the proposed method, and the impacts of selection intensity, preference degree and threshold on the evolutionary stable distribution are analyzed. Comparative simulations show that the proposed method outperforms GWO, DE, and NSGA-II, achieving 17.18% higher expected utility than NSGA-II and reducing evolutionary stable times by 25% in large-scale scenario.
KW - Multi-chain markov
KW - Public goods game (PGG)
KW - Strategy update rule
KW - Unmanned aerial vehicles (UAVs)
KW - Weapon-target assignment
UR - http://www.scopus.com/inward/record.url?scp=85219027022&partnerID=8YFLogxK
U2 - 10.1016/j.dt.2025.01.014
DO - 10.1016/j.dt.2025.01.014
M3 - 文章
AN - SCOPUS:85219027022
SN - 2096-3459
VL - 48
SP - 221
EP - 237
JO - Defence Technology
JF - Defence Technology
ER -