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Citation

Královec, J. and Šimandl, M. : Filtering, prediction and smoothing with point-mass approach . 16th IFAC symposium on automatic control in aerospace, p. 377-382, State University of Aerospace Instrumentation, Saint-Petersburg, 2004.

Abstract

The point-mass method for nonlinear state estimation is re-examined. Several aspects of the methods are treated and algorithms for multi-step prediction and smoothing based on the point-mass filtering algorithm are derived. Thus solution of all three estimation problems, i.e. filtering, prediction and smoothing, is unified within the point-mass framework. An anticipative technique for adaptation of support grid is presented. This techniquea automatically sets the number of grid points according to a future behaviour of the system and with respect to the user-defined accuracy of pdf approximation.

Detail of publication

Title: Filtering, prediction and smoothing with point-mass approach
Author: Královec, J. ; Šimandl, M.
Language: English
Date of publication: 14 Jun 2004
Year: 2004
Type of publication: Papers in proceedings of reviewed conferences
Title of journal or book: 16th IFAC symposium on automatic control in aerospace
Page: 377 - 382
Publisher: State University of Aerospace Instrumentation
Address: Saint-Petersburg
Date: 14 Jun 2004 - 16 Jun 2004
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Keywords

stochastic systems, state estimation, nonlinear filters, probability density function, estimation algorithms

BibTeX

@INPROCEEDINGS{KralovecJ_2004_Filteringprediction,
 author = {Kr\'{a}lovec, J. and \v{S}imandl, M.},
 title = {Filtering, prediction and smoothing with point-mass approach},
 year = {2004},
 publisher = {State University of Aerospace Instrumentation},
 journal = {16th IFAC symposium on automatic control in aerospace},
 address = {Saint-Petersburg},
 pages = {377-382},
 url = {http://www.kky.zcu.cz/en/publications/KralovecJ_2004_Filteringprediction},
}