Monte Carlo filters for non-linear state estimation

Authors
Bolviken, E Acklam, PJ Christophersen, N Stordal, JM
Citation
E. Bolviken et al., Monte Carlo filters for non-linear state estimation, AUTOMATICA, 37(2), 2001, pp. 177-183
Citations number
21
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
AUTOMATICA
ISSN journal
00051098 → ACNP
Volume
37
Issue
2
Year of publication
2001
Pages
177 - 183
Database
ISI
SICI code
0005-1098(200102)37:2<177:MCFFNS>2.0.ZU;2-P
Abstract
The application of Monte Carlo techniques to Bayesian state estimation is d iscussed. A simple theory for the Monte Carlo uncertainty is developed show ing that the number of Monte Carlo replications does not in principle have to be large. A recursive on-line algorithm based on rejection sampling is g iven and improved versions suggested. The methods are illustrated on a non- linear pendulum with measurement saturation. (C) 2000 Elsevier Science Ltd. All rights reserved.