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Mathematics Research Report MRR95-026
An Algorithm For Kalman Filtering And Smoothing With Diagonal Input Covariance Matrices
Inge Soderkvist
Abstract:
A new square-root algorithm for Kalman filtering and smoothing is derived.
The new algorithm is a modification of the information filter presented by
Paige
and Saunders [SIAM J. Num.Anal. 12 (1977), pp. 180-193] and can be used
when the
input covariance matrices are diagonal. Potential ill-conditioning, caused by
different sizes of the input covariances, is handled using techniques for
solving
weighted and constrained least squares problems. These techniques imply
that the
new algorithm can handle singular covariance matrices as well as singular
information
matrices.
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