DocumentCode :
2231489
Title :
Comparison of resampling schemes for particle filtering
Author :
Douc, R. ; Cappe, Olivier
Author_Institution :
Ecole Polytech., Palaiseau, France
fYear :
2005
fDate :
15-17 Sept. 2005
Firstpage :
64
Lastpage :
69
Abstract :
This contribution is devoted to the comparison of various resampling approaches that have been proposed in the literature on particle filtering. It is first shown using simple arguments that the so-called residual and stratified methods do yield an improvement over the basic multinomial resampling approach. A simple counter-example showing that this property does not hold true for systematic resampling is given. Finally, some results on the large-sample behavior of the simple bootstrap filter algorithm are given. In particular, a central limit theorem is established for the case where resampling is performed using the residual approach.
Keywords :
Monte Carlo methods; particle filtering (numerical methods); signal sampling; bootstrap filter algorithm; multinomial resampling approach; particle filtering; resampling schemes; residual methods; sequential Monte Carlo methods; stratified methods; Computational modeling; Density functional theory; Filtering; Filters; Image processing; Monte Carlo methods; Signal processing; Signal processing algorithms; Sliding mode control; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on
ISSN :
1845-5921
Print_ISBN :
953-184-089-X
Type :
conf
DOI :
10.1109/ISPA.2005.195385
Filename :
1521264
Link To Document :
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