Observatorio de I+D+i UPM

Descripción
This paper presents a theoretical framework for track building in multiple-target scenarios from the Bayesian point of view. It is assumed that the number of targets is fixed and known. We propose two optimal methods for building tracks sequentially. The first one uses the labelling of the current multitarget state estimate that minimizes the mean-square labeled optimal subpattern assignment error. This method requires knowledge of the posterior density of the vector-valued state. The second assigns the labeling that maximizes the probability that the current multi-target state estimate is optimally linked with the available tracks at the previous time step. In this case, we only require knowledge of the random finite-set posterior density without labels.
Internacional	Si
JCR del ISI	Si
Título de la revista	Ieee Transactions on Signal Processing
ISSN	1053-587X
Factor de impacto JCR	3,198
Información de impacto
Volumen	62
DOI	10.1109/TSP.2014.2364013
Número de revista	24
Desde la página	6366
Hasta la página	6379
Mes	DICIEMBRE
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• Autor: Ángel F. García Fernández (Curtin University, Australia)
• Autor: Mark R. Morelande (The University of Melbourne, Australia)
• Autor: Jesus Grajal De la Fuente (UPM)

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