Performance Analysis of General Tracking Algorithms
1994 (English)Report (Other academic)
A general family of tracking algorithms for linear regression models is studied. It includes the familiar LMS (gradient approach), RLS (recursive least squares) and KF (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 whole time interval, including the transient and the approximation error can be explicitly calculated.
Place, publisher, year, edition, pages
Linköping: Linköping University , 1994. , 16 p.
LiTH-ISY-R, ISSN 1400-3902 ; 1664
Linear regression models, Kalman filters, Covariance matrices
Cybernetik Informationsteori, Maskinelement Servomekanismer Automation
IdentifiersURN: urn:nbn:se:liu:diva-55130ISRN: LITH-ISY-R-1664OAI: oai:DiVA.org:liu-55130DiVA: diva2:315717