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

Alexandre Lepoutre 1, 2 Olivier Rabaste 1 François Le Gland 2
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.
Type de document :
Communication dans un congrès
Proceedings of the 2012 Workshop on Sensor Data Fusion: Trends, Solutions, Applications, Bonn 2012, Sep 2012, Bonn, Germany. pp.13-18, 2012, 〈10.1109/SDF.2012.6327901〉
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https://hal.inria.fr/hal-00911789
Contributeur : Francois Le Gland <>
Soumis le : vendredi 29 novembre 2013 - 20:07:40
Dernière modification le : jeudi 11 janvier 2018 - 06:24:24

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Alexandre Lepoutre, Olivier Rabaste, François Le Gland. A particle filter for target arrival detection and tracking in track-before-detect. Proceedings of the 2012 Workshop on Sensor Data Fusion: Trends, Solutions, Applications, Bonn 2012, Sep 2012, Bonn, Germany. pp.13-18, 2012, 〈10.1109/SDF.2012.6327901〉. 〈hal-00911789〉

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