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Conference papers

Optimized instrumental density for particle filter 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 the detection and tracking of a single target in Track-Before-Detect with a particle filter from radar measures. The studied particle filter solves the detection problem by introducing a marko-vian variable that stands for the presence or absence of the target. We claim that the usual prior density used as instrumental density is not suitable here, and we propose an efficient particle filter based on a relevant proposal density based on detection and estimation considerations that aims at extracting all the available information from the measurements. This filter leads to dramatically improved performance compared to the particle filter based on the classic instrumental distribution, both in terms of detection and estimation.
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Submitted on : Friday, November 29, 2013 - 8:09:40 PM
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Alexandre Lepoutre, Olivier Rabaste, François Le Gland. Optimized instrumental density for particle filter in track-before-detect. Proceedings of the 9th IET Data Fusion Target Tracking Conference, London 2012, May 2012, London, United Kingdom. ⟨10.1049/cp.2012.0418⟩. ⟨hal-00911788⟩



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