Optimal linear estimation and data fusion

被引：6
|
作者：
Elliott, RJ [1 ]
Van der Hoek, J
机构：
[1] Univ Calgary, Haskayne Sch Business, Calgary, AB T2N 1N4, Canada
[2] Univ Adelaide, Dept Appl Math, Adelaide, SA 5005, Australia
来源：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2006年 / 51卷 / 04期
关键词：
data fusion; optimal linear estimation;
D O I：
10.1109/TAC.2006.872768
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Optimal mean square linear estimators are determined for general uncorrelated noise. We allow the noise variance matrix in the observation process to be singular. This requires properties of generalized inverses which are developed in Section It. The proofs appear to be new. When there are two observation sequences the optimal method of recursively fusing the two is determined. We derive a new formula for the covariance of the two estimates which then provides exact dynamics for a fused estimate.
引用
收藏
页码：686 / 689
页数：4
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