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DOI: 10.5445/IR/1000038517
DOI: 10.3182/20140824-6-ZA-1003.01568

Recursive Generalized Total Least Squares with Noise Covariance Estimation

Rhode, Stephan; Bleimund, Felix; Gauterin, Frank

We propose a recursive generalized total least-squares (RGTLS) estimator that is used in parallel with a noise covariance estimator (NCE) to solve the errors-in-variables problem for multi-input-single-output linear systems with unknown noise covariance matrix. Simulation experiments show that the suggested RGTLS with NCE procedure outperforms the common recursive least squares (RLS) and recursive total instrumental variables (RTIV) estimators when all measured inputs and the measured output are noisy. Moreover, when all measured inputs are noise-free, RGTLS with NCE performs similarly to RLS, which in this special case is the optimal estimator, and again RTIV was inferior compared with the RGTLS and NCE procedure.

Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Proceedingsbeitrag
Jahr 2014
Sprache Englisch
Identifikator URN: urn:nbn:de:swb:90-385171
KITopen ID: 1000038517
Erschienen in 19th World Congress of the International Federation of Automatic Control, 24-29 August 2014, Cape Town, South Africa
Bemerkung zur Veröffentlichung NOTICE: this is the author's version of a work that was accepted for publication in Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in
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