面向防守作战的来袭目标威胁评估OA
Threat assessment of incoming targets for defensive operations
针对防守作战中来袭目标的威胁评估问题,提出了一种基于加权动态贝叶斯网络(Weighted Dynamic Bayes-ian Network,WDBN)和逼近理想解排序法(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)的目标威胁评估方法.首先,选取威胁评估指标并对指标之间的内在关联进行分析,将指标进行离散化处理,通过组合赋权法求取指标的综合权重.其次,构建 DBN 用于威胁等级的推理,并在条件概率表中融入指标综合权重.最后,针对 DBN 存在的排序困难问题,引入 TOPSIS 方法对 WDBN 的推理结果进行排序.仿真结果表明,相比于直接使用 DBN,本文方法推理的结果更符合真实战场情形.
A target threat assessment method based on Weighted Dynamic Bayesian Network(WDBN)and Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is proposed for threat assessment of incoming targets in defen-sive operations.First,select threat assessment indicators and analyze the inherent correlation between the indicators.Dis-cretize the indicators and use the combination weighting method to obtain the comprehensive weight of the indicators.Sec-ond,construct a DBN for threat level inference and incorporate the comprehensive weights of the indicators into the condi-tional probability table.Finally,in response to the sorting difficulty of DBN,the TOPSIS method is introduced to sort the in-ference results of WDBN.Compared with directly using the DBN,simulation results show that the algorithm proposed in this paper is more in line with the actual battlefield situation.
翟明圆;应淮冰;王武阳;何立栋
中国航空工业集团公司沈阳飞机设计研究所,辽宁 沈阳 110034||东北大学信息科学与工程学院,辽宁 沈阳 110819南京理工大学自动化学院,江苏 南京 210094南京理工大学自动化学院,江苏 南京 210094南京理工大学自动化学院,江苏 南京 210094
军事科技
威胁评估加权动态贝叶斯网络逼近理想解排序法组合赋权威胁排序
threat assessmentweighted dynamic Bayesian networkTOPSIScombination weighting methodthreat se-quencing
《指挥控制与仿真》 2026 (3)
11-17,7
国家自然科学基金(61973163)
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