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Non-Linear Filtering based on Observations from Gaussian 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.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2011 (English)In: Proceedings of the 2011 IEEE Aerospace Conference, 2011, , 6 p.Conference paper, Published paper (Refereed)
Abstract [en]

We consider a class of non-linear filtering problems, where the observation model is given by a Gaussian process rather than the common non-linear function of the state and measurement noise. The new observation model can be considered as a generalization of the standard one with correlated measurement noise in both time and space. We propose a particle filter based approach with a measurement update step that requires a memory of past observations which can be truncated using a moving window to obtain a finite-dimensional filter with arbitrarily good accuracy. The validity of the conceptual solution is proved via simulations on a one dimensional tracking problem and implementation issues are discussed.

Place, publisher, year, edition, pages
2011. , 6 p.
Keyword [en]
Gaussian processes, Nonlinear filters, Particle filtering (numerical methods)
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-76075DOI: 10.1109/AERO.2011.5747440ISBN: 978-1-4244-7350-2 (print)OAI: oai:DiVA.org:liu-76075DiVA: diva2:512104
Conference
2011 IEEE Aerospace Conference, Big Sky, MT, USA, 5-12 March, 2011
Projects
CADICS
Available from: 2012-03-26 Created: 2012-03-26 Last updated: 2013-07-10

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Gustafsson, FredrikSaha, Saikat

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  • nn-NB
  • sv-SE
  • Other locale
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