Statistically Linearized Recursive Least Squares

Matthieu Geist (1) , Olivier Pietquin (1)

1 SUPELEC-Campus Metz

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.

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⟩