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Tracking and Detecting moving weak Targets

Naima Amrouche 1, 2 Ali Khenchaf 1 Daoud Berkani 2
1 Lab-STICC_ENSTAB_MOM_PIM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : Detect and tracking of moving weak targets is a complicated dynamic state estimation problem whose difficulty is increased in case of high clutter conditions or low signal to noise ratio (SNR). In this case, the track-before-detect filter (TBDF) that uses unthresholded measurements considers as an effective method for detecting and tracking a single target under low SNR conditions. In this paper, a particle filter based track-before-detect (PF-TBD) method is proposed to address the problem of detection and tracking with unthersholded data and a binary variable of the existence of the target for two motion models. Simulation results using image measurements based on TBD scenarios are also presented to demonstrate the capability of the proposed approach.
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https://hal-ensta-bretagne.archives-ouvertes.fr/hal-01727779
Contributeur : Marie Briec <>
Soumis le : vendredi 9 mars 2018 - 15:30:14
Dernière modification le : mercredi 24 juin 2020 - 16:19:51

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Naima Amrouche, Ali Khenchaf, Daoud Berkani. Tracking and Detecting moving weak Targets. Advances in Science, Technology and Engineering Systems Journal, Advances in Science Technology and Engineering Systems Journal (ASTESJ), 2018, 3 (1), pp.467-471. ⟨10.25046/aj030157⟩. ⟨hal-01727779⟩

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