基于灰双矩阵博弈的舰载无人机编队协同对海突击目标分配

Grey Bi-Matrix Game Theory Based Target Assignment for Ship-Based UAV Formation in Coordinated Air-to-Sea Attacking

针对舰载无人机编队协同对海突击目标分配问题中,由于预警探测水平限制、信息的不完全、人的偏好、有限理性等因素导致的灰色情形,建立了攻防对抗双方的分配策略集和支付矩阵,构建了基于灰双矩阵博弈的舰载无人机编队协同对海突击目标分配模型,并设计了新的粒子位置更新公式对粒子群算法进行改进。分别用遗传算法、传统粒子群算法和改进的粒子群算法进行仿真,对比结果表明,改进后的粒子群算法能够跳出局部最优解,快速收敛到全局最优解,所建立的模型能够较好地解决目标分配决策中的灰色问题,是灰双矩阵博弈理论在目标分配领域的重要应用,仿真结果证明了模型的实用有效性和算法的高效性。

Grey situation commonly exists in target assignment of ship-based UAV formation in coordinated air-to-sea attacking due to limit of early-warning and detection level,incomplete information,and favor and bounded rationality of decision-makers. Aiming at the problem,the target assignment strategy set and payoff matrix of UAV formation and surface ship formation were established. Then,a model of target assignment of ship-based UAV formation for coordinated air-to-sea attacking was constructed based on grey bi-matrix game theory. An improved PSO algorithm was designed to solve the problem with reformed particle location updating formula. Simulations were carried out by using GA,traditional PSO and the improved PSO algorithm respectively. The results indicate that： 1） The improved PSO algorithm can avoid local optimum solution and converge to the globally optimum solution; and 2） The grey bi-matrix game theory based target assignment model can well solve the grey problem in target assignment. The results prove the practicability of the model and the effectiveness of the algorithm.