Title :
An Adaptive Iterated Kalman Filter
Author :
Zhang, YongAn ; Zhou, Di ; Duan, Guang-Ren
Author_Institution :
Shenzhen Grad. Sch., Harbin Inst. of Technol., Shenzhen
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 :
Kalman filters; adaptive control; discrete time systems; nonlinear control systems; statistical analysis; adaptive iterated Kalman filter; discrete-time nonlinear systems; modified Sage-Husa noise statistics estimator; recursive filtering; 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
Print_ISBN :
7-302-13922-9
Electronic_ISBN :
7-900718-14-1
DOI :
10.1109/CESA.2006.4281916
