一种不确定性动态环境下的威胁评估方法  

A Threat Assessment Method in Uncertain Dynamic Environments

作　　者：杨妹 王秉坤 张中杰 曾焱 黄健[1] Yang Mei;Wang Bingkun;Zhang Zhongjie;Zeng Yan;Huang Jian(College of Intelligence Science and Technology,National University of Defense Technology,Changsha 410073,China;Northwest Institute of Mechanical&Electrical Engineering,Xianyang 712099,China)

机构地区：[1]国防科技大学智能科学学院,湖南长沙410073 [2]西北机电工程研究所,陕西咸阳712099

出　　处：《系统仿真学报》2024年第12期2741-2754,共14页Journal of System Simulation

基　　金：国防科技重点实验室基金(6142003202311);国家自然科学基金青年基金(62103425);湖南省自然科学基金(2022JJ40559)。

摘　　要：针对战争复杂系统存在动态不确定性,提出一种基于先验信息和动态观测结果的威胁评估方法。对先验信息进行数据挖掘获得战场态势先验知识并构建装备关联置信矩阵;构建传感器模型,综合考虑先验知识和观测结果的情况下使用贝叶斯方法动态更新当前态势情况下蓝方实体的数量;确定威胁评价指标和指标权重,使用TOPSIS法完成威胁评估。该方法能较好地描述复杂多变的动态战场环境,并充分利用先验信息和动态观测结果对探测区域或探测位置附近探测盲区进行威胁评估。通过案例仿真分析验证了该方法的可行性。A threat assessment method based on priori information and dynamic observation results is studied for the existence of dynamic uncertainty in complex war systems.The data mining is applied to obtain prior knowledge on the battlefield situation and construct an equipment-related confidence matrix.The sensor model is constructed to dynamically update the number of blue-side entities under the current situation by using the Bayesian method and considering both intelligence and observation results.The threat evaluation indicators and their weights are determined,and the TOPSIS method is used to finish the threat assessment.This method can well describe the complex and changing dynamic battlefield environment and make full use of priori information and dynamic observation results for threat assessment of the detection area or the undetectable location nearby.The feasibility of this method is verified through case simulation analysis.

关 键 词：威胁评估 数据挖掘 贝叶斯 TOPSIS法 不确定性 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]