Title :
Optimality for data fusion of detectors using Voronoi cells
Author_Institution :
Embry-Riddle Aeronaut. Univ., Prescott, AZ, USA
fDate :
10/1/2000 12:00:00 AM
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;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
