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基于Bayes网络的多源信息融合方法在精度评定中的应用
引用本文:曹渊,张士峰,胡正东.基于Bayes网络的多源信息融合方法在精度评定中的应用[J].飞行器测控学报,2008(5):80-85.
作者姓名:曹渊  张士峰  胡正东
作者单位:国防科技大学航天与材料工程学院,湖南长沙410073
摘    要:提出了一种基于多源验前信息融合的Bayes精度评定方法。利用Bayes网络进行多源验前信息融合时,能够结合现场试验数据,对信息加权因子做出较为合理的推断。根据验前及验后数据,通过Bayes网络中的MC—MC方法可以快速地获取各变量的验后统计特性,达到估计现场试验精度的目的。因此,基于多源验前信息融合的Bayes方法可用于解决小样本下的精度评定问题,仿真结果表明了该方法的有效性。

关 键 词:Bayes网络  MCMC  信息融合  加权因子  精度评定

Application of Multi-source Test Information Fusion in Bayesian Network-based Accuracy Evaluation
CAO Yuan,ZHANG Shi-feng,HU Zheng-dong.Application of Multi-source Test Information Fusion in Bayesian Network-based Accuracy Evaluation[J].Journal of Spacecraft TT&C Technology,2008(5):80-85.
Authors:CAO Yuan  ZHANG Shi-feng  HU Zheng-dong
Institution:(College of Aerospace and Material Engineering, National University of Defense Technology, Changsha, Hunan Province 410073)
Abstract:This paper presents a method of multi-source test information fusion for Bayesian precision evaluation. Reasonable inference can be attained for information importance factor in combination with site test data when using Bayesian network in multi-source test information. Based on pre-test and post-test data, MCMC algorithm in Bayesian network is used to quickly get the post-test statistical characteristics of variables for evaluation of site test accuracy. Therefore, the method can he used in accuracy evaluation especially when the sample number is small. Simulation results show the effectiveness of the method proposed in this paper.
Keywords:Bayesian Network  MCMC  Information Fusion  Importance Factor  Accuracy Evaluation
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