A particle filter for target arrival detection and tracking in track-before-detect

Alexandre Lepoutre; Olivier Rabaste; François Le Gland

doi:10.1109/SDF.2012.6327901

Conference papers

A particle filter for target arrival detection and tracking in track-before-detect

Alexandre Lepoutre ^{1, 2} Olivier Rabaste ¹ François Le Gland ²

1 ONERA - The French Aerospace Lab [Châtillon]

2 ASPI - Applications of interacting particle systems to statistics

IRMAR - Institut de Recherche Mathématique de Rennes, Inria Rennes – Bretagne Atlantique

Abstract : 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.

Document type :

Conference papers

Domain :

Mathematics [math] / Probability [math.PR]

Complete list of metadata

https://hal.inria.fr/hal-00911789
Contributor : Francois Le Gland <>
Submitted on : Friday, November 29, 2013 - 8:07:40 PM
Last modification on : Tuesday, March 16, 2021 - 3:42:04 PM

A particle filter for target arrival detection and tracking in track-before-detect

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A particle filter for target arrival detection and tracking in track-before-detect

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