基于改进遗传算法的无人战车跃进位置决策

针对无人战车协同进攻战斗中如何自主确定跃进位置和射击位置的问题，构建无人战车自主确定跃进位 置和射击位置决策数学模型。综合考虑战场地形环境、敌方兵力分布、跃进距离、跃进方向、友邻间火力协同等因 素，提出一种保留最优个体的自适应多种群遗传算法(genetic algorithm，GA)对模型进行求解。实验结果表明：该模 型能够实现无人战车自主确定跃进位置和射击位置的目的；提出的改进遗传算法具有全局搜索能力强、收敛速度快、 稳定性好等优点；对无人作战装备自主能力的研究和提升具有一定参考价值。

Position Decision of Unmanned Combat Vehicle Based on Improved Genetic Algorithm

Aiming at the problem of how to determine the position of jumping and shooting independently in the cooperative attack combat of unmanned combat vehicle (UCAV), a decision-making mathematical model for determining the position of jumping and shooting independently is constructed. Considering the battlefield terrain environment, enemy force distribution, leap distance, leap direction, fire coordination between friendly neighbors and other factors, an adaptive multi-population genetic algorithm (GA) with the best individual is proposed to solve the model. The experimental results show that the model can achieve the purpose of determining the jump position and shooting position of unmanned combat vehicle autonomously. The proposed improved genetic algorithm has the advantages of strong global search ability, fast convergence speed and good stability, which has a certain reference value for the research and promotion of autonomous capability of unmanned combat equipment.