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State estimation of nonlinear systems using the Unscented Kalman Filter
Almeida J.1; Oliveira P.1; Silvestre C.2; Pascoal A.1
2015
Conference Name2015 IEEE Region 10 Conference
Source PublicationTENCON 2015 - 2015 IEEE Region 10 Conference
Volume2016-January
Conference Date1-4 Nov. 2015
Conference PlaceMacao, China
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
Language英语
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Document TypeConference paper
专题DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Affiliation1.Universidade de Lisboa
2.Universidade de Macau
推荐引用方式
GB/T 7714
Almeida J.,Oliveira P.,Silvestre C.,et al. State estimation of nonlinear systems using the Unscented Kalman Filter[C],2015.
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