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Citation

Šimandl, M. and Straka, O. : Sampling density design for particle filters . System identification 2003, IFAC Proceedings Volumes, p. 175-180, Elsevier , Oxford, 2004.

Abstract

The particle filters for state estimation of discrete time dynamic stochastic systems are treated. The stress is laid on design of sampling pdf which is significant for quality of the particle filters. A new functional sampling density design based on utilization of transition and measurement pdf's is proposed. The functional approach compares two pdf's of a reference variable which are obtained by transformation of the transition and measurement pdf's, using Kullback J-divergence. The functional approach to sampling density function synthesis can be understood as improvement of the sampling density design of the auxiliary particle filter which uses point estimate of the transition pdf only. High quality of the functional particle filter with respect to the bootstrap and the auxiliary particle filter is illustrated in a numerical example.

Detail of publication

Title: Sampling density design for particle filters
Author: Šimandl, M. ; Straka, O.
Language: English
Date of publication: 27 Aug 2003
Year: 2004
Type of publication: Book Chapters
Title of journal or book: System identification 2003
Edition: IFAC Proceedings Volumes
Page: 175 - 180
ISBN: 0-08-043709-5
Publisher: Elsevier
Address: Oxford
Date: 27 Aug 2003 - 29 Aug 2003
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Keywords

state estimation, nonlinear systems, particle filters, sampling density

BibTeX

@INBOOK{SimandlM_2004_Samplingdensity,
 author = {\v{S}imandl, M. and Straka, O.},
 title = {Sampling density design for particle filters},
 year = {2004},
 publisher = {Elsevier },
 journal = {System identification 2003},
 address = {Oxford},
 pages = {175-180},
 ISBN = {0-08-043709-5},
 url = {http://www.kky.zcu.cz/en/publications/SimandlM_2004_Samplingdensity},
}