Observatorio de I+D+i UPM

Descripción
This paper addresses the problem of approximating the posterior probability density function of two targets after a crossing from the Bayesian perspective such that the information about target labels is not lost. To this end, we develop a particle filter that is able to maintain the inherent multimodality of the posterior after the targets have moved in close proximity. Having this approximation available, we are able to extract information about target labels even when the measurements do not provide information about target's identities. In addition, due to the structure of our particle filter, we are able to use an estimator that provides lower optimal subpattern assignment (OSPA) errors than usual estimators.
Internacional	Si
Nombre congreso	14th International Conference on Information Fusion
Tipo de participación	960
Lugar del congreso	Chicago, Illinois, USA
Revisores	Si
ISBN o ISSN	978-0-9824438-2-8
DOI
Fecha inicio congreso	05/07/2011
Fecha fin congreso	08/07/2011
Desde la página	795
Hasta la página	802
Título de las actas	Particle filter for extracting target label information when targets move in close proximity

Esta actividad pertenece a memorias de investigación

• Autor: Ángel Froilán García Fernández (UPM)
• Autor: Jesus Grajal De la Fuente (UPM)

• Creador: Grupo de Investigación: Microondas y Radar
• Departamento: Señales, Sistemas y Radiocomunicaciones