A particle filter for target arrival detection and tracking in Track-Before-Detect

In this paper, we address the problem of detecting the appearance time of a target and tracking its state with a particle filter in the Track-Before-Detect context. We show that it is possible to model the problem as a quickest detection change problem in a Bayesian framework. In this case, the post...

Full description

Saved in:
Bibliographic Details
Main Authors: Lepoutre, A., Rabaste, O., Le Gland, F.
Format: Conference Proceeding
Language:English
Subjects:
Approximation methods
Mathematical model
Proposals
Radar tracking
Signal to noise ratio
Target tracking
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we address the problem of detecting the appearance time of a target and tracking its state with a particle filter in the Track-Before-Detect context. We show that it is possible to model the problem as a quickest detection change problem in a Bayesian framework. In this case, the posterior density of the target time appearance is a mixture where each component represents the hypothesis that the target arrived at a given time. As the posterior density is intractable in practice, we propose to approximate each component of the mixture by a particle filter, and we show that the weights of the mixture can be computed recursively thanks to quantities provided by the different particle filters. The overall filter yields good performance.
DOI:10.1109/SDF.2012.6327901