Some aspects of fusion in estimation theory

Author

Hall, Eric B. ; Wessel, Alan E. ; Wise, Gary L.

Author_Institution

Dept. of Electr. Eng., Southern Methodist Univ., Dallas, TX, USA

Volume

37

Issue

2

fYear

1991

fDate

3/1/1991 12:00:00 AM

Firstpage

420

Lastpage

422

Abstract

The problem of fusing or combining various estimates to obtain a single good estimate is investigated. The problem of fusion in estimation theory is addressed, and several examples using common distributions in which virtually any method of fusion would be useless in approximating the random variable of interest are presented. A theorem which, for a very general situation, shows that fusion resulting in an almost surely exact approximation is always possible is presented. In particular, this result addresses the situation in which the data consists of the random variable of interest corrupted by additive Gaussian noise and the random variable of interest could be any second-order random variable. Finally, an example which illustrates the utility of this result is presented

Keywords

estimation theory; information theory; random noise; additive Gaussian noise; estimation theory; fusion; information theory; random variable; Estimation theory; Extraterrestrial measurements; Mathematics; Military computing; Random variables; Spatial resolution; Statistics;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.75268

Filename

75268