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Méthodes d'estimation statistique pour le suivi de cibles à l'aide d'un réseau de capteurs

Adrien Ickowicz 1 
1 ASPI - Applications of interacting particle systems to statistics
UR1 - Université de Rennes 1, Inria Rennes – Bretagne Atlantique , CNRS - Centre National de la Recherche Scientifique : UMR6074
Abstract : This thesis is concerned with the estimation of the dynamical parameters of one or multiple targets moving through an area which is ''watched'' by a sensor network. The first part deal with performance analysis for data association, in a target tracking environment. Effects of misassociation are considered in a simple (linear) multiscan framework so as to provide closed-form expressions of the probability of correct association. Via rigorous calculations the effect of dimensioning parameters is analyzed. Remarkably, it is possible to derive very simple expressions of the probability of correct association which are independent of the scenario kinematic parameters. In a second part, we are especially interested by fusing binary information at the network level. This binary information is related to the local target behavior; i.e. its distance from a given sensor is increasing (-) or decreasing (+). However, in this rich framework we choose to focus on even simpler observations so as to put in evidence the limits and the difficulties of the decentralized binary framework. More specifically, the binary sequences {-,+} can be (locally) summarized by the times of closest point approach (cpa). So, we consider that the available observations, at the network level, are the estimated values of the cpa times. The analysis is also greatly simplified if we assume that the target motion is rectilinear and uniform or a leg-by-leg one. In the case of a single-leg trajectory, we resort to a simple maximum-likelihood estimator, while for the case of multiple-leg trajectories other methods are presented. Then, we finally present a new algorithm for target tracking within a binary sensor network. The novel tracking method is proposed and its performance through a very classical trajectory model is evaluated. We finally try to extend the algorithm to multiple target tracking.
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Submitted on : Tuesday, January 24, 2012 - 5:53:11 PM
Last modification on : Thursday, January 20, 2022 - 4:15:31 PM
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  • HAL Id : tel-00482418, version 3


Adrien Ickowicz. Méthodes d'estimation statistique pour le suivi de cibles à l'aide d'un réseau de capteurs. Mathématiques [math]. Université Rennes 1, 2010. Français. ⟨NNT : ⟩. ⟨tel-00482418v3⟩



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