About: Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters

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About: Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters Goto Sponge NotDistinct Permalink

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	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. 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. (en)
Title	Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters (en)
skos:prefLabel	Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters (en)
skos:notation	RIV/67985556:_____/13:00393047!RIV14-GA0-67985556
http://linked.open...avai/predkladatel	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GAP102/11/0437)
http://linked.open...iv/cisloPeriodika	6
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Šmídl, Václav
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	86376
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/13:00393047
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Unknown Noise Statistics; Adaptive Filtering; Marginalized Particle Filter; Bayesian Conjugate prior (en)
http://linked.open.../riv/klicoveSlovo	Adaptive Filtering Bayesian Conjugate prior Marginalized Particle Filter Unknown Noise Statistics
http://linked.open...odStatuVydavatele	NL - Nizozemsko
http://linked.open...ontrolniKodProRIV	[5C684B31E707]
http://linked.open...i/riv/nazevZdroje	Automatica
http://linked.open...in/vavai/riv/obor	BC
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	5 (xsd:int)
http://linked.open...vavai/riv/projekt	Control and Parameter Identification of AC Electric Drives under Critical Operating Conditions
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	49
http://linked.open...iv/tvurceVysledku	Šmídl, Václav Gustafsson, F. Sáha, S. Lundquist, C. Ökzan, E.
http://linked.open...ain/vavai/riv/wos	000319540500005
issn	0005-1098
number of pages	10 (xsd:int)
http://bibframe.org/vocab/doi	10.1016/j.automatica.2013.02.046

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