Hawk-rabbit game architecture for unmanned aerial vehicle swarm multi-target defense under uncertain attack targets.
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| Název: | Hawk-rabbit game architecture for unmanned aerial vehicle swarm multi-target defense under uncertain attack targets. |
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| Autoři: | Yue, Wei1 (AUTHOR) yuewei811010@163.com, Zhang, Xiaoyong1 (AUTHOR) |
| Zdroj: | Aerospace Science & Technology. Sep2025, Vol. 164, pN.PAG-N.PAG. 1p. |
| Témata: | *DRONE aircraft, *SCALABILITY, *RABBITS, *AUCTIONS, *GAMES |
| Abstrakt: | • A Hawk-Rabbit game architecture is presented for UAV swarm multi-target defense, addressing uncertainty in attack targets and enhancing pursuit efficiency compared to the Hawk-Pigeon game [ 26–29 ]. • An interval number-based task allocation model is proposed to handle interval costs caused by uncertain attack targets, using adaptive interval sorting to strengthen adaptability to fuzzy situation assessment. • The dynamic auction-based two-stage iterative allocation (DATIA) algorithm is devised for real-time task allocation. It allocates high-threat attackers via dynamic auction and dynamically reallocates remaining attackers through greedy iteration, promoting collaboration and improving system scalability. This paper explores the allocation problem in multi-target defense tasks for unmanned aerial vehicle (UAV) swarms, concentrating on mitigating the impact of the uncertainty interval cost caused by the uncertainty attack target on the allocation outcomes. Firstly, a hawk-rabbit game architecture is constructed to map the multi-target defense problem to the predatory behavior patterns of hawks hunting rabbits. Within this architecture, the interception strategies and attack tactics for both defenders and attackers are formulated. Based on the hawk-rabbit game, a task allocation model using interval numbers is constructed to optimize defense and attack efficacy by minimizing flight and time costs. Then, an adaptive interval sorting method is presented, which utilizes geometric distance-based and possibility-based ways to optimize the sorting of interval costs. Finally, the dynamic auction-based two-stage iterative allocation (DATIA) algorithm is designed to accomplish real-time task allocation. The DATIA algorithm supports distributed decision-making and is suitable for large-scale UAV swarm operations in target defense scenario. Simulation experiments in multiple scenarios indicate that the proposed method significantly surpasses the existing attack-defense game strategy in terms of interception time, resource utilization, and interception effectiveness. [ABSTRACT FROM AUTHOR] |
| Databáze: | Academic Search Index |
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