DocumentCode
508434
Title
An improvement on the iterated Kalman filter
Author
Niu Xin-liang ; Zhao Guo-qing ; Liu Yuan-hua ; Chang Hong
Author_Institution
Res. Inst. of ECM, Xidian Univ., Xi´an
fYear
2009
fDate
20-22 April 2009
Firstpage
1
Lastpage
4
Abstract
An improved iterated Kalman filter (IKF) is proposed to reduce the sensitivity of the filter to the initial estimate error. According to the essence of the IKF, i.e., the Gauss-Newton method is used to approximate a maximum likelihood estimate, a new update method is obtained. Simulations show that the improved IKF has better performance than the IKF when the initial estimate error is large.
Keywords
Gaussian processes; Kalman filters; Newton method; iterative methods; maximum likelihood estimation; Gauss-Newton method; iterated Kalman filter; maximum likelihood estimate; Gauss-Newton method; Kalman filter; improvement; iterated method; maximum likelihood estimate;
fLanguage
English
Publisher
iet
Conference_Titel
Radar Conference, 2009 IET International
Conference_Location
Guilin
ISSN
0537-9989
Print_ISBN
978-1-84919-010-7
Type
conf
Filename
5367295
Link To Document