摘要
空地多目标火力分配是机载空地多目标攻击系统的核心。分析了空地多目标火力分配问题的特点,提出了不同的最优评价标准,并根据其对应的目标函数建立了3种空地多目标火力分配模型。以自适应蚁群算法为基础,利用遗传算子进行交叉变异操作,结合粒子群算法的思想修改信息素更新规则,给出了融合算法求解空地多目标火力分配问题的步骤。通过仿真实验验证了融合算法的有效性。
The air-to-ground multi-target firepower assignment is the core of the airborne multi-target attack system.The characteristics of air-to-ground multi-target firepower assignment problem are analyzed,and different optimal evaluation criteria are proposed.According to the corresponding objective functions,three air-to-ground multi-target firepower assignment models are established.Based on the adaptive ant colony algorithm,the genetic operator is used to carry out cross-mutation operation,and the pheromone updating rule is modified by referring to the idea of Particle Swarm Optimization(PSO) algorithm.The steps of the fusion algorithm to solve the air-to-ground multi-target firepower assignment problem are given.The effectiveness of the fusion algorithm is verified by simulation experiments.
作者
李天龙
张军超
LI Tian-long;ZHANG Jun-chao(The First Aircraft Institute AVIC, Xi'an 710089, China)
出处
《电光与控制》
CSCD
北大核心
2019年第11期56-59,共4页
Electronics Optics & Control
关键词
空地多目标攻击
火力分配
蚁群算法
遗传算法
粒子群算法
air-to-ground multi-target attack
firepower assignment
ant colony algorithm
genetic algorithm
particle swarm optimization
