Journal article

BLUE, BLUP and the Kalman filter: some new results

PJG Teunissen, A Khodabandeh



In this contribution, we extend 'Kalman-filter' theory by introducing a new BLUE-BLUP recursion of the partitioned measurement and dynamic models. Instead of working with known state-vector means, we relax the model and assume these means to be unknown. The recursive BLUP is derived from first principles, in which a prominent role is played by the model's misclosures. As a consequence of the mean state-vector relaxing assumption, the recursion does away with the usual need of having to specify the initial state-vector variance matrix. Next to the recursive BLUP, we introduce, for the same model, the recursive BLUE. This extension is another consequence of assuming the state-vector means unkn..

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University of Melbourne Researchers


Awarded by Australian Research Council

Funding Acknowledgements

P.J.G. Teunissen is the recipient of an Australian Research Council Federation Fellowship (project number FF0883188). The research of A. Khodabandeh was carried out whilst a Curtin International Research Scholar at Curtin's GNSS Research Centre. All this support is gratefully acknowledged.