DocumentCode
1238639
Title
Consistency checks for particle filters
Author
van der Heijden, F.
Author_Institution
Fac. of EEMCS, Twente Univ., Enschede, Netherlands
Volume
28
Issue
1
fYear
2006
Firstpage
140
Lastpage
145
Abstract
An "inconsistent" particle filter produces - in a statistical sense - larger estimation errors than predicted by the model on which the filter is based. Two test variables are introduced that allow the detection of inconsistent behavior. The statistical properties of the variables are analyzed. Experiments confirm their suitability for inconsistency detection.
Keywords
Monte Carlo methods; particle filtering (numerical methods); state estimation; statistical analysis; Kalman state estimation; Monte Carlo approach; consistency checks; particle filters; statistical analysis; statistical sense-larger estimation errors; Estimation error; Fault detection; Filtering; Hidden Markov models; Mathematical model; Noise measurement; Particle filters; Predictive models; State estimation; Testing; Index Terms- Particle filtering; consistency checks; fault detection; model validation.; modeling errors; Algorithms; Artificial Intelligence; Computer Simulation; Models, Statistical; Pattern Recognition, Automated; Signal Processing, Computer-Assisted; Stochastic Processes; Systems Theory;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.2006.5
Filename
1542038
Link To Document