Title :
A particle-filter-based detection scheme
Author :
Boers, Yvo ; Driessen, Hans
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;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2003.817175
