面向自杀式无人机饱和攻击的海空跨域无人协同反制策略

Cooperative Countermeasure Strategy of Sea-Air Cross-Domain Unmanned Platforms for Saturation Attack of Suicide UAVs

针对海洋环境下反制自杀式无人机饱和攻击问题,文中研究了目标数量远超我方情况下的海空跨域无人平台协同反制策略,提出一种结合改进的遗传算法与联盟形成博弈的协同算法。首先根据海空跨域无人平台攻击特性与运动特性,结合最大最小策略设计代价函数;然后结合任务需求对遗传算法进行改进,对交叉和变异过程进行引导和限制,在提升遗传算法效率的基础上生成可行的反制方案;最后设计联盟形成规则,通过联盟之间的成员变动使各联盟达到纳什稳定状态,在算子数量较多的情况下仍能使反制方案被持续稳定优化。仿真对比实验表明所提策略具有可行性和优越性,能在目标遭受饱和攻击时提供合理高效的反制方案,可为大规模跨域无人集群作战研究提供参考。

In view of saturation attacks of anti-suicide unmanned aerial vehicles(UAVs)in the marine environment,this paper studied the cooperative countermeasure strategy of sea-air cross-domain unmanned platforms under the condition that the number of targets far exceeded ours and proposed a cooperative algorithm combining improved genetic algorithm and coalition formation game.Firstly,according to the attack and motion characteristics of the sea-air cross-domain unmanned platform,the cost function was designed by combining the maximum and minimum strategies.Then,the genetic algorithm was improved according to the task requirements,and the crossover and mutation processes were guided and restricted.A feasible countermeasure scheme was generated by improving the efficiency of the genetic algorithm.Finally,the coalition formation rules were designed,and the coalitions reached Nash stability via changing members between the coalitions.The countermeasure scheme could still be continuously and stably optimized for many operators.The simulation comparison experiments show that the proposed strategy is feasible and superior and can provide a reasonable and efficient countermeasure scheme when the target is subjected to a saturation attack.This can provide a reference for research on large-scale cross-domain unmanned swarm combat.