DocumentCode
785645
Title
A particle-filter-based detection scheme
Author
Boers, Yvo ; Driessen, Hans
Volume
10
Issue
10
fYear
2003
Firstpage
300
Lastpage
302
Abstract
In this paper, we present a new result that can be used for detection purposes. We show that when estimating the a posteriori probability density of a possible signal in noise by means of a particle filter, the output of the filter, i.e., the unnormalized weights, can be used to approximately construct the likelihood ratio, which arises in many different detection schemes.
Keywords
approximation theory; filtering theory; maximum likelihood estimation; probability; signal detection; a posteriori estimation; likelihood ratio approximation; nonGaussian noise; nonlinear systems; particle filter; probability density; signal detection; unnormalized weights; Current measurement; Density measurement; Filtering; Nonlinear dynamical systems; Particle filters; Radar detection; Radar tracking; Signal generators; Signal to noise ratio; Testing;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2003.817175
Filename
1232725
Link To Document