UKF design and stability for nonlinear stochastic systems with correlated noises

Author

Xu, Jiahe ; Dimirovski, Georgi M. ; Jing, Yuanwei ; Shen, Chao

Author_Institution

Northeastern Univ., Shenyang

fYear

2007

fDate

12-14 Dec. 2007

Firstpage

6226

Lastpage

6231

Abstract

Based on the standard unscented Kalman filter (UKF), the modified UKF is presented for nonlinear stochastic systems with correlated noises. The modified UKF consists of the prediction equations and the measurement equations, and holds the sigma points chosen by unscented transformation (UT). The stability of the modified UKF for the nonlinear stochastic system with correlated noises is analyzed. It is proved that under certain conditions, the estimation error of the UKF remains bounded. These results are verified by using Matlab simulations on two numerical example systems.

Keywords

Kalman filters; control system synthesis; nonlinear filters; nonlinear systems; prediction theory; stability; stochastic systems; correlated noises; estimation error; nonlinear stochastic systems; prediction equations; stability; unscented Kalman filter design; unscented transformation; Chaos; Estimation error; Filters; Gaussian noise; Measurement standards; Noise measurement; Nonlinear equations; Stability analysis; Stochastic systems; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2007 46th IEEE Conference on

Conference_Location

New Orleans, LA

ISSN

0191-2216

Print_ISBN

978-1-4244-1497-0

Electronic_ISBN

0191-2216

Type

conf

DOI

10.1109/CDC.2007.4434109

Filename

4434109