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State estimation of nonlinear systems using the Unscented Kalman Filter
J. Almeida1; P. Oliveira1; C. Silvestre1; A. Pascoal2
2016-01-07
Conference NameTENCON 2015 - 2015 IEEE Region 10 Conference
Source PublicationTENCON 2015 - 2015 IEEE Region 10 Conference
Volume2016-January
Conference Date1-4 Nov. 2015
Conference PlaceMacao, China
PublisherIEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Abstract

This paper addresses the problem of estimating the state of a nonlinear system from measurements that are perturbed by a random source of noise. The Extended Kalman Filter is a type of all-purpose filter that tries to solve this problem by dealing with a linearized version of the system. A new methodology proposed in [1], named Unscented Kalman Filter, is presented. It uses the so-called unscented transformation to better describe the stochastic evolution of the state of the system. The aim of this paper is to compare and discuss the performance of each filter when applied to state estimation of a simplified model of the DELMAC autonomous surface craft.

DOI10.1109/TENCON.2015.7372796
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000380489200086
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
Corresponding AuthorJ. Almeida
Affiliation1.Faculty of Science and Technology, University of Macau, Taipa Macau, China
2.Universidade de Lisboa, Lisboa, Lisboa, PT
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
J. Almeida,P. Oliveira,C. Silvestre,et al. State estimation of nonlinear systems using the Unscented Kalman Filter[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA,2016.
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