Statistically Linearized Recursive Least Squares

Abstract : This article proposes a new interpretation of the sigmapoint kalman filter (SPKF) for parameter estimation as being a statistically linearized recursive least-squares algorithm. This gives new insight on the SPKF for parameter estimation and particularly this provides an alternative proof for a result of Van der Merwe. On the other hand, it legitimates the use of statistical linearization and suggests many ways to use it for parameter estimation, not necessarily in a least-squares sens.
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Conference papers
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https://hal-supelec.archives-ouvertes.fr/hal-00553168
Contributor : Sébastien van Luchene <>
Submitted on : Thursday, January 6, 2011 - 4:22:30 PM
Last modification on : Thursday, March 29, 2018 - 11:06:04 AM

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Matthieu Geist, Olivier Pietquin. Statistically Linearized Recursive Least Squares. MLSP 2010, Aug 2010, Kittilä, Finland. pp.272-276, ⟨10.1109/MLSP.2010.5589236⟩. ⟨hal-00553168⟩

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