用混合蛙跳算法的智能防空火力分配  

Intelligent Anti-Aircraft Firepower Assignment Based on Shuffled Frog Leaping Algorithm

作　　者：韩占朋[1] 王玉惠[1] 姜长生[1] 吴庆宪[1] 

机构地区：[1]南京航空航天大学自动化学院,南京210016

出　　处：《电光与控制》2012年第12期10-13,共4页Electronics Optics & Control

基　　金：国家自然科学基金(11102080);航空科学基金(20095152028);南京航空航天大学基本科研业务费专项科研项目(NS2010077);光电控制技术国家重点实验室资助项目

摘　　要：结合混合蛙跳算法对防空作战火力分配问题进行了探索。在火力分配建模的前提下,应用改进的混合蛙跳算法求解模型。首先根据空袭目标特点,采用十进制编码方式设计模型求解矩阵,由该矩阵可直接得到火力决策阵,其特点是求解精度高,可锁定任意火力单元的打击对象。在原混合蛙跳算法的基础上,通过引入一个与迭代次数相关的可变步长σ,使算法的执行过程从多点变异方式转换到单点变异方式,从而使算法具有更强的健壮性。在满足单个火力单元射击约束的前提下,根据算法原理给出具体的求解方案和步骤。通过实例仿真验证了算法的可行性和有效性。与遗传算法及改进的遗传算法相比较,混合蛙跳算法具有更快的收敛速度和精度。The firepower assignment in air defense combat was studied based on shuffled frog leaping algorithm. An anti-aircraft firepower assignment model was established, and an improved shuffled frog leaping algorithm was used to figure it out. According to the characteristics of the targets, a solution matrix with higher precision was designed in decimal encoding, which could confirm the target of any firepower unit. Based on the original algorithm, a variable step length factor σ related to iteration times was designed, which could change the implementation process from multi-variation to single point mutation, and made the whole process more robust. The specific solution and steps based on improved SFLA were put forward in condition of the fire shooting constraints. The simulation results verify the feasibility and effectiveness of the proposed algorithm. Compared with genetic algorithm and the improved GA, SFLA shows a higher convergence speed and accuracy.

关 键 词：自动控制 火力分配 混合蛙跳算法 鲁棒性 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计] E833[军事—战术学]