Title :
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
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;
Conference_Titel :
Decision and Control, 2007 46th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-1497-0
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2007.4434109
