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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.
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Conference papers
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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

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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, ⟨10.1109/SDF.2012.6327901⟩. ⟨hal-00911789⟩

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