Scalar-Weighted Fusion Estimators for Systems with Multiple Sensors and Multiple Delayed Measurements

被引：3

作者：

Lv, Nan ^{[1
]}

Sun, Shuli ^{[1
]}

机构：

[1] Heilongjiang Univ, Dept Automat, Harbin 150080, Peoples R China

来源：

PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009) | 2009年

关键词：

FILTER; NOISE;

D O I：

10.1109/CDC.2009.5399696

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper is concerned with the distributed fusion estimation problem for discrete-time stochastic linear system with multiple sensors having multiple delayed measurements and correlated noise. Distributed weighted fusion optimal estimators are given based on local optimal estimators from single sensor and the optimal scalar-weighted fusion algorithm in the linear minimum variance sense. Compared with the augmented optimal estimators, the distributed fusion estimators with scalar weights are more reliable and have the reduced computation cost since they have the parallel structure. The estimation error cross-covariance matrices between any two-sensor subsystems are derived. Applying to a tracking system with three sensors shows the effectiveness.

引用

页码：7599 / 7602

页数：4

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