BP神经网络的布撒器末端修正  

A Study on Terminal Correction of Airborne Dispenser Based on BP Neural Network

作　　者：褚进[1] 张安[1] 齐玲辉[1] 陈瑞军[2] 

机构地区：[1]西北工业大学电子信息学院,西安710129 [2]中国白城兵器试验中心,吉林白城137001

出　　处：《火力与指挥控制》2012年第10期74-76,80,共4页Fire Control & Command Control

基　　金：航天支撑技术基金资助项目(2010-HT-XGD)

摘　　要：针对布撒器开舱点位置解算及子弹药减速伞延时解算所需时间长的问题,引入了BP神经网络算法,建立了子弹药的数学模型和BP神经网络解算模型,并进行了布撒器末端修正的仿真分析。仿真结果表明:运用BP神经网络算法计算的结果误差较小,并且大大缩短了在线解算的时间,进一步提升了布撒器的作战效能。According to the calculation of the airborne dispenser breakingbulk＇s position and the delay of submunition＇s drag-parachute taking long time, BP neural network is introduced. Mathematical model of submunition and computing model based on BP neural network is set up, and terminal correction of airborne dispenser is analyzed according to simulation. Simulations results indicate that using BP neural network can get smaller calculate error and much shorter time in online resolution, and the operation effectiveness of airborne dispenser is further promoted.

关 键 词：开舱点位置 子弹药延时 BP神经网络 精度 作战效能 

分 类 号：TJ765.4[兵器科学与技术—武器系统与运用工程]