DocumentCode
1556636
Title
An Efficient Two-Stage Sampling Method in Particle Filter
Author
Cheng, Qi ; Bondon, Pascal
Author_Institution
Univ. Paris-Sud, Paris, France
Volume
48
Issue
3
fYear
2012
fDate
7/1/2012 12:00:00 AM
Firstpage
2666
Lastpage
2672
Abstract
We present a modified bootstrap filter (MBF) to draw particles in the particle filter (PF). The proposal distribution for each particle involves sampling from the state-space model a number of times, and then selecting the sample with the highest measurement likelihood. Numerical examples show that this filter outperforms the bootstrap filter (BF) with the same computational complexity when the state noise has a large variance.
Keywords
computational complexity; particle filtering (numerical methods); signal sampling; state-space methods; statistical analysis; MBF; Monte Carlo method; PF; computational complexity; measurement likelihood; modified bootstrap filter; particle filter; state noise; state-space model; two-stage sampling method; Approximation methods; Estimation; Gaussian distribution; Kalman filters; Monte Carlo methods; Noise; Particle filters;
fLanguage
English
Journal_Title
Aerospace and Electronic Systems, IEEE Transactions on
Publisher
ieee
ISSN
0018-9251
Type
jour
DOI
10.1109/TAES.2012.6237616
Filename
6237616
Link To Document