DocumentCode
990750
Title
The iterated Kalman filter update as a Gauss-Newton method
Author
Bell, Bradley M. ; Cathey, Frederick W.
Author_Institution
Appl. Phys. Lab., Washington Univ., Seattle, WA, USA
Volume
38
Issue
2
fYear
1993
fDate
2/1/1993 12:00:00 AM
Firstpage
294
Lastpage
297
Abstract
It is shown that the iterated Kalman filter (IKF) update is an application of the Gauss-Newton method for approximating a maximum likelihood estimate. An example is presented in which the iterated Kalman filter update and maximum likelihood estimate show correct convergence behavior as the observation becomes more accurate, whereas the extended Kalman filter update does not
Keywords
Kalman filters; approximation theory; convergence; iterative methods; maximum likelihood estimation; state estimation; Gauss-Newton method; convergence; iterated Kalman filter update; maximum likelihood estimate; state estimation; Aerospace electronics; Extraterrestrial measurements; Least squares approximation; Least squares methods; Maximum likelihood estimation; Newton method; Recursive estimation; Sea measurements; Space technology; State estimation;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/9.250476
Filename
250476
Link To Document