UNSCENTED KALMAN FILTER REVISITED - HERMITE-GAUSS QUADRATURE APPROACH

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00195666" target="_blank" >RIV/68407700:21230/12:00195666 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

UNSCENTED KALMAN FILTER REVISITED - HERMITE-GAUSS QUADRATURE APPROACH

Popis výsledku v původním jazyce

Kalman filter is a frequently used tool for linear state estimation due to its simplicity and optimality. It can further be used for fusion of information obtained from multiple sensors. Kalman filtering is also often applied to nonlinear systems. As thedirect application of bayesian functional recursion is computationally not feasible, approaches commonly taken use either a local approximation - Extended Kalman Filter based on linearization of the non-linear model - or the global one, as in the case of Particle Filters. An approach to the local approximation is the so called Unscented Kalman Filter. It is based on a set of symmetrically distributed sample points used to parameterise the mean and the covariance. Such filter is computationally simple and no linearization step is required. Another approach to selecting the set of sample points based on decorrelation of multivariable random variables and Hermite-Gauss Quadrature is introduced in this paper. This approachprovides an addit

Název v anglickém jazyce

UNSCENTED KALMAN FILTER REVISITED - HERMITE-GAUSS QUADRATURE APPROACH

Popis výsledku anglicky

Kalman filter is a frequently used tool for linear state estimation due to its simplicity and optimality. It can further be used for fusion of information obtained from multiple sensors. Kalman filtering is also often applied to nonlinear systems. As thedirect application of bayesian functional recursion is computationally not feasible, approaches commonly taken use either a local approximation - Extended Kalman Filter based on linearization of the non-linear model - or the global one, as in the case of Particle Filters. An approach to the local approximation is the so called Unscented Kalman Filter. It is based on a set of symmetrically distributed sample points used to parameterise the mean and the covariance. Such filter is computationally simple and no linearization step is required. Another approach to selecting the set of sample points based on decorrelation of multivariable random variables and Hermite-Gauss Quadrature is introduced in this paper. This approachprovides an addit

Druh

D - Stať ve sborníku

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

<a href="/cs/project/GAP103%2F11%2F1353" target="_blank" >GAP103/11/1353: Odhad stavu dynamických stochastických systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of 15th International Conference on Information Fusion

ISBN

9780982443842

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

1-5

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Singapore

Datum konání akce

9. 7. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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