空天防御2025，Vol.8Issue(1)：62-70,9.
基于GA-BP神经网络的防空导弹实时目标分配方法
Target Assignment Method of Air Defense Missile Based on GA-BP Neural Network
孙栋一 1蒲宇亭 1章建榜1
作者信息
- 1. 中国人民解放军95010部队,广东 汕头 515000
- 折叠
摘要
Abstract
Given the great dynamic change in the modern air defense combat environment,the air defense missile weapon system requires real-time online target allocation.In this study,a real-time target allocation method for air defense missiles based on a genetic algorithm(GA)optimized back propagation(BP)neural network was proposed.Firstly,the optimization model of the air defense missile target allocation problem was established by employing the number of air defense missile weapons and damage probability,and the maximum damage effectiveness was set as the optimization goal.Then,the air defense missile target allocation framework based on the GA-BP neural network was constructed.The optimal weights and thresholds of the BP neural network were acquired using a genetic algorithm to optimize the BP neural network.The accurate and efficient allocation of threat targets to the current air defense missile was achieved from neural network prediction.Finally,the optimized neural network was applied for simulation analysis,allowing real-time target allocation under the battlefield situation,and verifying the effectiveness and practicability of the proposed method.关键词
防空导弹/遗传算法/BP神经网络/目标分配/辅助决策Key words
air defense missile/genetic algorithm/BP neural network/target assignment/assistant decision分类
信息技术与安全科学引用本文复制引用
孙栋一,蒲宇亭,章建榜..基于GA-BP神经网络的防空导弹实时目标分配方法[J].空天防御,2025,8(1):62-70,9.
