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Communication dans un congrès

Detection and Tracking of Targets under Low SNR

Naïma Amrouche 1, 2 Ali Khenchaf 1, 2 Daoud Berkani 3
1 Lab-STICC_ENSTAB_MOM_PIM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
2 Pôle STIC_REMS
ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne
Abstract : Target tracking in the time is a difficult problem of dynamic state estimation; the problem is more complex in a low signal to noise ratio (SNR) or in high clutter conditions. An efficient approach for target detection and tracking under low signal to noise ratio (SNR) conditions is the Track-Before-Detect (TBDF) filter. This paper proposes to use the TBD method based on particle filtering includes unthresholded data and a binary variable of the existence of the target in the estimating target state for two motion model. Using simulations it is shown that with this method, it is possible to detect and track the target in low signal to noise ratio.
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Communication dans un congrès
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https://hal.archives-ouvertes.fr/hal-01653314
Contributeur : Annick Billon-Coat <>
Soumis le : vendredi 1 décembre 2017 - 12:01:12
Dernière modification le : mercredi 24 juin 2020 - 16:19:51

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Naïma Amrouche, Ali Khenchaf, Daoud Berkani. Detection and Tracking of Targets under Low SNR. ICIT'2017, Mar 2017, Ontario, Canada. ⟨10.1109/ICIT.2017.7915496⟩. ⟨hal-01653314⟩

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