A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Optimal minimal-order least-squares estimators via the general two-stage Kalman filter
2001
IEEE Transactions on Automatic Control
Preserved Fulltext
A direct derivation of the optimal minimal-order leastsquares estimator (OMOLSE) is presented using the recently developed general two-stage Kalman filter (GTSKF). Using this new result, the reduced-order estimators of O'Reilly and Fairman are readily shown to be equivalent. A practical implementation issue to consider these two estimators is also addressed. Index Terms-Least-squares estimator, minimal-order estimator, reduced-order estimator, two-stage Kalman filter.
doi:10.1109/9.964689
fatcat:qiu3uystpbfk5av46zthhas5ie