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
fDate :
2/1/1993 12:00:00 AM
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;
Journal_Title :
Automatic Control, IEEE Transactions on
