Performance Analysis of General Tracking Algorithms
1995 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 40, no 8, 1388-1402 p.Article in journal (Refereed) Published
A general family of tracking algorithms for linear regression models is studied. It includes the familiar least mean square gradient approach, recursive least squares, and Kalman filter based estimators. The exact expressions for the quality of the obtained estimates are complicated. Approximate, and easy-to-use, expressions for the covariance matrix of the parameter tracking error are developed. These are applicable over the whole time interval, including the transient, and the approximation error can be explicitly calculated.
Place, publisher, year, edition, pages
1995. Vol. 40, no 8, 1388-1402 p.
Kalman filters, Adaptive control, Adaptive signal processing, Covariance matrices, Parameter estimation, Tracking
IdentifiersURN: urn:nbn:se:liu:diva-56343DOI: 10.1109/9.402230OAI: oai:DiVA.org:liu-56343DiVA: diva2:318616
FunderSwedish Research Council