Evaluation of Measurement Uncertainty Based on Bayesian Information Fusion

被引：0

作者：

Wang Shan ^{[1
]}

Chen Xiaohuai ^{[1
]}

Yang Qiao ^{[1
]}

机构：

[1] Sch Instrument Sci & Optoelect Engn, Hefei 230009, Peoples R China

来源：

SIXTH INTERNATIONAL SYMPOSIUM ON PRECISION MECHANICAL MEASUREMENTS | 2013年 / 8916卷

关键词：

Bayesian Statistical Principle; information fusion; uncertainty assessment; simulation and verification;

D O I：

10.1117/12.2035725

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper raises a new method for evaluating uncertainty that taking count of both the record and the data. By using Bayesian Statistical Principle, the prior distribution and the posterior one, provided by the record and the data, were combined together. The statistical characteristics parameter estimation was descended from the posterior distribution, so that a formula of the uncertainty, which combined the advantages of type A and B, was acquired. By simulation and verification, this measurement shows great advantages compared with the others, especially to small size of data analysis.

引用

页数：8