The fusion of redundant SEVA measurements

被引：32

作者：

Duta, M ^{[1
]}

Henry, M ^{[1
]}

机构：

[1] Univ Oxford, Dept Engn Sci, Invensys Univ Technol Ctr, Oxford OX1 3PJ, England

来源：

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | 2005年 / 13卷 / 02期

关键词：

maximum clique problem; self-validating (SEVA) sensors; sensor fusion;

D O I：

10.1109/TCST.2004.840448

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The self-validating (SEVA) sensor carries out an internal quality assessment, and generates, for each measurement, standard metrics for its quality, including online uncertainty. This paper discusses consistency checking and data fusion between several SEVA sensors observing the same measurand. Consistency checking is shown to be equivalent to the maximum clique problem, which is NP-hard, but a linear approximation is described. A technique called uncertainty extension is proposed which causes a smooth reduction in the influence of outliers as they become increasingly inconsistent with the majority.

引用

页码：173 / 184

页数：12