基于改进遗传算法的无人战车跃进位置决策 |
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引用本文: | 闫晓东.基于改进遗传算法的无人战车跃进位置决策[J].兵工自动化,2023,42(3). |
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作者姓名: | 闫晓东 |
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作者单位: | 陆军装甲兵学院兵器与控制系 |
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摘 要: | 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。
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关 键 词: | 自主无人作战 位置决策 多种群遗传算法 自适应遗传算法 |
收稿时间: | 2022/11/26 0:00:00 |
修稿时间: | 2022/12/28 0:00:00 |
Position Decision of Unmanned Combat Vehicle
Based on Improved Genetic Algorithm |
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Abstract: | 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. |
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Keywords: | autonomous unmanned combat position decision multi-population genetic algorithm adaptive
genetic algorithm |
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