Memorias de investigación
Communications at congresses:
Mixture truncated unscented Kalman filtering
Year:2012

Research Areas
  • Electronic technology and of the communications

Information
Abstract
This paper proposes a computationally efficient nonlinear filter that approximates the posterior probability density function (PDF) as a Gaussian mixture. The novelty of this filter lies in the update step. If the likelihood has a bounded support made up of different regions, we can use a modified prior PDF, which is a mixture, that meets Bayes? rule exactly. The central idea of this paper is that a Kalman filter applied to each component of the modified prior mixture can improve the approximation to the posterior provided by the Kalman filter. In practice, bounded support is not necessary.
International
Si
Congress
15th International Conference on Information Fusion, FUSION 2012
960
Place
Singapore
Reviewers
Si
ISBN/ISSN
978-1-4673-0417-7
Start Date
07/09/2012
End Date
12/09/2012
From page
479
To page
486
Proceedings of 15th International Conference on Information Fusion 2012
Participants
  • Autor: Ángel Froilán García Fernández UPM
  • Autor: M.R. Morelande University of Melbourne, Australia
  • Autor: Jesus Grajal De la Fuente UPM

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Microondas y Radar
  • Departamento: Señales, Sistemas y Radiocomunicaciones