Skip to content

Detail of publication


Straka Ondřej and Šimandl Miroslav : Adaptive Particle Filter with Fixed Empirical Density Quality . Proceedings of the 17th IFAC World Congress, vol. ;, p. 6484-6489, IFAC, Seoul, 2008.


The paper deals with the particle filter in state estimation of a discrete-time nonlinear non-Gaussian system. The goal of the paper is to design a sample size adaptation technique to guarantee the quality of an empirical probability density function (pdf) which approximates a target filtering pdf. The quality is measured by inaccuracy (cross-information) between the empirical pdf and the filtering pdf. It is shown that for increasing sample size the inaccuracy converges to the Shannon differential entropy (SDE) of the filtering pdf. The proposed technique adapts the sample size to keep a difference between the inaccuracy and the SDE within pre-specified bounds with a pre-specified probability. The particle filter with the proposed sample size adaptation technique is illustrated in a numerical example.

Detail of publication

Title: Adaptive Particle Filter with Fixed Empirical Density Quality
Author: Straka Ondřej ; Šimandl Miroslav
Language: English
Year: 2008
Type of publication: Papers in proceedings of reviewed conferences
Title of journal or book: Proceedings of the 17th IFAC World Congress
Číslo vydání: ;
Page: 6484 - 6489
ISBN: 978-3-902661-00-5
Publisher: IFAC
Address: Seoul
Date: 11 Jul 2008
2011-03-15 16:21:32 / 2011-03-15 16:21:32 / 1


Particle filtering, Monte Carlo methods, Estimation, filtering, Adaptation, Sample size


 author = {Straka Ond\v{r}ej and \v{S}imandl Miroslav},
 title = {Adaptive Particle Filter with Fixed Empirical Density Quality},
 year = {2008},
 publisher = {IFAC},
 journal = {Proceedings of the 17th IFAC World Congress},
 address = {Seoul},
 volume = {;},
 pages = {6484-6489},
 ISBN = {978-3-902661-00-5},
 url = {},