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Marginalized Particle Filter for Dependent Gaussian Noise Processes
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2012 (English)In: Proceedings of the 2012 IEEE Aerospace Conference, 2012Conference paper, Published paper (Refereed)
Abstract [en]

The theory and the applications of the marginalized particle filter (MPF) have attracted much research attention during the last decade. However, the existing MPF framework does not cover dependent process and measurement noises. This dependency is perhaps more common in practice than is acknowledged in the literature. In this article, we propose a general framework for MPF, covering both cases of dependent and independent noises. As a consequence, MPF with independent noises is a special case of this general framework. The treatment of dependency always provides `extra' information to the state estimation tasks. This beneficial effect is shown through a numerical example.

Place, publisher, year, edition, pages
2012.
Keyword [en]
Gaussian processes, Particle filtering
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-87585DOI: 10.1109/AERO.2012.6187212ISI: 000309105302035ISBN: 978-1-4577-0556-4 (print)OAI: oai:DiVA.org:liu-87585DiVA: diva2:589540
Conference
2012 IEEE Aerospace Conference, Big Sky, Montana, USA, 3-10 March, 2012
Available from: 2013-01-18 Created: 2013-01-18 Last updated: 2013-07-10Bibliographically approved

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Saha, SaikatGustafsson, Fredrik

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