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.<>
Efficient numerical algorithm for steady-state Kalman covariance
IEEE Transactions on Aerospace and Electronic Systems ; 24 , 6 ; 815-817
1988-11-01
239746 byte
Article (Journal)
Electronic Resource
English
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