摘要
态势指标的运动是动态和高度非线性的,甚至无法给出一个确切的数学描述。采用模糊数学这一在军事决策领域中普遍应用的方法,给出了一种态势分析的通用方法。采取模糊因果聚类的方法,利用物理传感器信息和历史数据(历史战例、作战模拟结果等)来静态求取阶段态势指标的估计值,同时采用模糊Bayes决策方法,利用非物理传感器的信息来修正估计,并且给出了优化的态势控制(作战决策)方法。
The movement of situation index is dynamic and of high nonlinearity,such that no exact mathematical model could be given.This paper puts forward a novel method for situation estimation,by means of fuzzy mathematics commonly used in military decisionmaking area.Fuzzy clustering by cause and effect is implemented in static situation analysis where the information such as former battles of combat simulation results are used for situation estimating.Moreover,the information from nonphysical sensors is employed to correct the former estimation,and an optimized method for decisionmaking is given through a fuzzy Bayes model.
出处
《火力与指挥控制》
CSCD
北大核心
2003年第3期31-34,共4页
Fire Control & Command Control
基金
河南省自然科学基金资助项目(0211050500)
关键词
数据融合
态势分析
威胁估计
模糊数学
data fusion,situation analysis,threat assessment,fuzzy mathemdtics
