Levenberg-Marquardt and Line-Search Extended Kalman Smoothers
Paper in proceeding, 2020

The aim of this article is to present Levenberg–Marquardt and line-search extensions of the classical iterated extended Kalman smoother (IEKS) which has previously been shown to be equivalent to the Gauss–Newton method. The algo- rithms are derived by rewriting the algorithm’s steps in forms that can be efficiently implemented using modified EKS iter- ations. The resulting algorithms are experimentally shown to have superior convergence properties over the classical IEKS.

Levenberg–Marquardt algorithm

Extended Kalman smoother

nonlinear estimation

line search


Simo Särkkä

Aalto University

Lennart Svensson

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

15206149 (ISSN)

Vol. 2020-May 5875-5879 9054686
9781509066315 (ISBN)

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Barcelona / Online, Spain,

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Areas of Advance

Information and Communication Technology


Subject Categories


Probability Theory and Statistics

Signal Processing



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Latest update

4/5/2022 6