Original title: Application of marginalized particle filter to linear-Gaussian problems with unknown model error covariance structure
Translated title: Aplikace opomíjeného praktického filtru pro lineárně Gausovské problémy s neznámým modelem chyb kovariantních struktur
Authors: Hofman, Radek
Document type: Papers
Conference/Event: Doktorandske dny 2008, Praha (CZ), 2008-11-07 / 2008-11-21
Year: 2008
Language: eng
Abstract: [eng] [cze]
The paper presents a scheme for estimation of spatio-temporal evolution of a quantity with unknown model error. Model error is estimated on basis of measured-minus-observed residuals evaluated upon measured and modeled values. Methods of Bayesian filtering are applied to the problem. The main contribution of this paper is application of general marginalized particle filter algorithm to the linear-Gaussian problem with unknown model error covariance structure. Methodology is demonstrated on the problem of modeling of spatio-temporal evolution of groundshine-dose from radionuclides deposited on terrain in long-time horizon. Článek se zabývá odhadováním spatio-temporální evoluce kvantity s neznámým modelem chyb.
Keywords: asimilation; linear-Gaussian problems
Project no.: CEZ:AV0Z10750506 (CEP), GA102/07/1596 (CEP)
Funding provider: GA ČR
Host item entry: Sborník workshopu doktorandů FJFI oboru Matematické inženýrství, ISBN 978-80-01-04195-6.

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2008/AS/hofman-application of marginalized particle filter to linear-gaussian problems with unknown model error covariance structure.pdf
Original record: http://hdl.handle.net/11104/0166132

Permalink: http://www.nusl.cz/ntk/nusl-39498


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Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers