A STATE ESTIMATOR FOR NONLINEAR STOCHASTIC SYSTEMS BASED ON DIRAC MIXTURE APPROXIMATIONS

Oliver C. Schrempf, Uwe D. Hanebeck

2007

Abstract

This paper presents a filter approach for estimating the state of nonlinear dynamic systems based on recursive approximation of posterior densities by means of Dirac mixture functions. The filter consists of a prediction step and a filter step. The approximation approach is based on a systematic minimization of a distance measure and is hence optimal and deterministic. In contrast to non-deterministic methods we are able to determine the optimal number of components in the Dirac mixture. A further benefit of the proposed approach is the consideration of measurements during the approximation process in order to avoid parameter degradation.

Paper Citation

in Harvard Style

C. Schrempf O. and D. Hanebeck U. (2007). A STATE ESTIMATOR FOR NONLINEAR STOCHASTIC SYSTEMS BASED ON DIRAC MIXTURE APPROXIMATIONS . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-972-8865-84-9, pages 54-61. DOI: 10.5220/0001629600540061

in Bibtex Style

@conference{icinco07,
author={Oliver C. Schrempf and Uwe D. Hanebeck},
title={A STATE ESTIMATOR FOR NONLINEAR STOCHASTIC SYSTEMS BASED ON DIRAC MIXTURE APPROXIMATIONS},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2007},
pages={54-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001629600540061},
isbn={978-972-8865-84-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - A STATE ESTIMATOR FOR NONLINEAR STOCHASTIC SYSTEMS BASED ON DIRAC MIXTURE APPROXIMATIONS
SN - 978-972-8865-84-9
AU - C. Schrempf O.
AU - D. Hanebeck U.
PY - 2007
SP - 54
EP - 61
DO - 10.5220/0001629600540061