Estimating model error covariance matrix parameters in extended Kalman filtering
The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user. In this paper, we study the filter likelihood technique for estimating the...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2014-09-01
|
Series: | Nonlinear Processes in Geophysics |
Online Access: | http://www.nonlin-processes-geophys.net/21/919/2014/npg-21-919-2014.pdf |