Levenberg-Marquardt and Line-Search Extended Kalman Smoothers
Paper in proceedings, 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.

line search

Levenberg–Marquardt algorithm

nonlinear estimation

Extended Kalman smoother

Author

Simo Särkkä

Aalto University

Lennart Svensson

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

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

15206149 (ISSN)

5875-5879 9054686

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

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Areas of Advance

Information and Communication Technology

Transport

Subject Categories

Telecommunications

Probability Theory and Statistics

Signal Processing

DOI

10.1109/ICASSP40776.2020.9054686

More information

Latest update

1/8/2021 4