Optimality for data fusion of detectors using Voronoi cells

Author

Hriljac, P.

Author_Institution

Embry-Riddle Aeronaut. Univ., Prescott, AZ, USA

Volume

36

Issue

4

fYear

2000

fDate

10/1/2000 12:00:00 AM

Firstpage

1396

Lastpage

1400

Abstract

The problem of optimal signal classification with distributed sensors and restricted communication channels is considered. The classifier is to decide if a signal is in one of several possible classes after being observed through a suite of sensors, each sensor giving rise to a soft classification. The local classifiers are assumed to be based on a Voronoi decomposition of the associated sensor output space. Conditions of optimality for both the classifier and the sensors are given.

Keywords

Bayes methods; computational geometry; distributed sensors; probability; quantisation (signal); sensor fusion; signal classification; Bayesian cost function; Voronoi cells; Voronoi decomposition; data fusion; distributed sensors; joint density function; optimal fusion rules; optimal signal classification; optimality conditions; probability; quantization; restricted communication channels; sensor output space; soft classification; suite of sensors; Bayesian methods; Communication channels; Cost function; Density functional theory; Detectors; Pattern classification; Quantization; Sensor fusion; System performance; Uncertainty;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.892688

Filename

892688