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多机协同对地攻击目标分配算法
引用本文:王强,丁全心,张安,齐玲辉.多机协同对地攻击目标分配算法[J].系统工程与电子技术,2012,34(7):1400-1405.
作者姓名:王强  丁全心  张安  齐玲辉
作者单位:1. 西北工业大学电子信息学院,陕西 西安 710129; 2. 中航工业洛阳电光设备研究所,河南 洛阳 471009
基金项目:航空科学基金,中航工业洛阳电光设备研究所光电控制技术重点实验室资助课题
摘    要:针对多机协同对地攻击目标分配问题及其特点,对二进制粒子群优化算法进行改进,提出了一种基于矩阵二进制粒子群优化算法的多机协同对地攻击目标分配算法。首先,通过攻击机机群在对地攻击过程中得到的毁伤收益与付出的生存力损耗建立了目标分配模型,然后根据该模型约束特点,建立问题解与分配矩阵即矩阵粒子之间的映射,最后根据粒子形式设计了新的位置更新方式。仿真结果说明,矩阵二进制粒子群算法能够快速地找到较优的目标分配方案,并保证解的有效性,满足问题的约束条件。

关 键 词:多机协同对地攻击  目标分配  分配矩阵  矩阵二进制粒子群优化

Target allocation algorithm for multi-cooperative air-to-ground attack
WANG Qiang , DING Quan-xin , ZHANG An , QI Ling-hui.Target allocation algorithm for multi-cooperative air-to-ground attack[J].System Engineering and Electronics,2012,34(7):1400-1405.
Authors:WANG Qiang  DING Quan-xin  ZHANG An  QI Ling-hui
Institution:1. School of Electronic Information, Northwestern Polytechnical University, Xi’an 710129, China; 2. Luoyang Institute of Electro-Optical Equipment, Aviation Industry Corporation of China, Luoyang 471009, China
Abstract:In view of the target allocation in multi-cooperative air-to-ground attack and its characteristics,a matrix binary particle swarm optimization based on improved binary particle swarm optimization is proposed for the target allocation in multi-cooperative air-to-ground attack.First of all,a model of target allocation is established using contrasting damage proceeds with viability wastage during multi-cooperative air-to-ground attack,and then the mapping of measure to allocation matrix,namely the matrix particles,is set up based on the restriction characteristics of this model.At last,a new update strategy for the position of particles is designed according to the style of the particle.The simulation results show that the matrix binary particle swarm optimization can find more preferably measure of target allocation rapidly,and the effectiveness of the measure can meet the requirements of restrict.
Keywords:multi-cooperative air-to-ground attack  target allocation  allocation matrix  matrix binary particle swarm optimization
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