Application in Damage Effect Evaluation of Early Warning Radar of Cloudy Bayesian Network Based on Dempster Shafer/AnalyticHierarchy Process Method

doi:10.12382/bgxb.2021.0036

Abstract

Abstract: Target damage evaluation can provide a credible basis for combat decision-making and is an indispensable key link in joint operations. A cloudy Bayesian network-based early warning radar damage evaluation model is established combining Bayesian network and cloud model to form a cloudy Bayesian network, and the cloud model is converted for various indicator system variables. For the defects of the traditional expert experience method in deriving the conditional probability, the dempster-shafer/analytic hierarchy process (DS/AHP） is used to determine the conditional probability value of each node. The variables are input into the cloudy Bayesian network, and the probability that the early warning radar belongs to each damage level is inferred. The proposed method is applied to the simulation calculation of the attack on the early warning radar system in the enemy's anti-missile system, and the effectiveness of cloudy Bayesian, network is compared with those of Bayesian netwok, fuzzy comprehensive evaluation method and cloud barysenter evaluation method. The simulated results show that cloudy bayesian network based on dempster-shafer/analytic hierarchy process method has a certain degree of improvement in terms of calculation rationality and calculation accuracy. It is an analysis method that can reasonably and effectively evaluate the damage effect of target.

Key words: cloudmodel, Bayesiannetwork, dempster-shafer/analytichierarchyprocess, damageeffectevaluation

CLC Number:

E920.8

DENG Liyuan, YANG Ping, LIU Weidong, WANG Jiangpeng. Application in Damage Effect Evaluation of Early Warning Radar of Cloudy Bayesian Network Based on Dempster Shafer/AnalyticHierarchy Process Method[J]. Acta Armamentarii, 2022, 43(4): 814-825.

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