Title :
An Adaptive Iterated Kalman Filter
Author :
Yong-An Zhang ; Di Zhou ; Guang-Ren Duan
Author_Institution :
Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China. zhangyongan@hit.edu.cn
Abstract :
The recursive filtering of discrete-time nonlinear systems in the presence of unknown noise statistical parameters is studied. By embedding the modified Sage-Husa noise statistics estimator into the iterated Kalman filter, an adaptive iterated Kalman filter is obtained. With iterative operations as well as the online estimation of unknown covariance of virtual noise, linearized error can be reduced. As a result, the estimation performance is improved. A numerical example shows the effectiveness of the proposed filter.
Keywords :
Adaptive control; Adaptive filters; Filtering; Noise measurement; Nonlinear systems; Programmable control; Recursive estimation; Statistics; Systems engineering and theory; Taylor series; Estimation; adaptive filter; extended Kalman filter; iterated Kalman filter;
Conference_Titel :
Computational Engineering in Systems Applications, IMACS Multiconference on
Conference_Location :
Beijing, China
Print_ISBN :
7-302-13922-9
Electronic_ISBN :
7-900718-14-1
DOI :
10.1109/CESA.2006.313591
