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dc.contributor.authorIckowicz, Adrien
dc.subjecttracking algorithmen
dc.subjectsingle index modelen
dc.subjectmaximum likelihooden
dc.subjectbinary sensorsen
dc.subjectparameter estimationen
dc.titleTrack estimation with binary derivative observationsen
dc.typeDocument de travail / Working paper
dc.description.abstractenWe focus in this paper in the estimation of a target trajectory defined by whether a time constant parameter in a simple stochastic process or a random walk with binary observations. The binary observation comes from binary derivative sensors, that is, the target is getting closer or moving away. Such a binary obervation has a time property that will be used to ensure the quality of a max-likelihood estimation, through single index model or classification for the constant velocity movement. In the second part of this paper we present a new algorithm for target tracking within a binary sensor network when the target trajectory is assumed to be modeled by a random walk. For a given target, this algorithm provides an estimation of its velocity and its position. The greatest improvements are made through a position correction and velocity analysis.en
dc.publisher.nameUniversité Paris-Dauphineen
dc.subject.ddclabelTraitement du signalen

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