DocumentCode
835433
Title
Efficient numerical algorithm for steady-state Kalman covariance
Author
Rogers, Steven R.
Author_Institution
Elta Electron., Ashdod
Volume
24
Issue
6
fYear
1988
fDate
11/1/1988 12:00:00 AM
Firstpage
815
Lastpage
817
Abstract
A stable, quadratically convergent numerical algorithm is presented for computing the steady-state covariance and gain matrices of the Kalman filter. The method is more rapidly convergent than standard Riccati integration techniques and is easier to implement than existing eigenvalue-eigenvector algorithms. The quadratic convergence is proved analytically and illustrated by a numerical example
Keywords
Kalman filters; convergence of numerical methods; iterative methods; matrix algebra; numerical methods; gain matrices; iterative method; numerical algorithm; quadratic convergence; steady-state Kalman covariance; Convergence; Covariance matrix; Eigenvalues and eigenfunctions; Iterative algorithms; Kalman filters; Noise measurement; Q measurement; Riccati equations; Steady-state; Symmetric matrices;
fLanguage
English
Journal_Title
Aerospace and Electronic Systems, IEEE Transactions on
Publisher
ieee
ISSN
0018-9251
Type
jour
DOI
10.1109/7.18649
Filename
18649
Link To Document