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Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters
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SYSNO ASEP 0393047 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters Author(s) Ökzan, E. (SE)
Šmídl, Václav (UTIA-B) RID, ORCID
Saha, S. (SE)
Lundquist, C. (SE)
Gustafsson, F. (SE)Number of authors 5 Source Title Automatica. - : Elsevier - ISSN 0005-1098
Roč. 49, č. 6 (2013), s. 1566-1575Number of pages 10 s. Publication form Print - P Language eng - English Country NL - Netherlands Keywords Unknown Noise Statistics ; Adaptive Filtering ; Marginalized Particle Filter ; Bayesian Conjugate prior Subject RIV BC - Control Systems Theory R&D Projects GAP102/11/0437 GA ČR - Czech Science Foundation (CSF) UT WOS 000319540500005 EID SCOPUS 84877574625 DOI 10.1016/j.automatica.2013.02.046 Annotation Knowledge of noise distribution is typically crucial for good estimation of a non-linear state-space model. However, properties of the noise process are often unknown in the majority of practical applications. Moreover, distribution of the noise may be non-stationary or state dependent, which prevents the use of off-line tuning methods. General estimation methods, such as particle filtering can be used to estimate the noise parameters, however at the price of heavy computational load. In this paper, we present an approach based on marginalized particle filtering where the noise parameters have analytical distribution. Explicit modeling of parameter non-stationarity is avoided and it is replaced by maximum-entropy estimation based on the assumption of slowly varying parameters. Properties of the resulting algorithm are illustrated on both a standard example and a navigation application based on odometry. The latter involves formulas for dead reckoning rotational speeds of two wheels with unknown radii. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2014
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