Levenberg-marquardt and line-search extended kalman smoothers

Simo Särkkä, Lennart Svensson

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

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 algorithms are derived by rewriting the algorithm's steps in forms that can be efficiently implemented using modified EKS iterations. The resulting algorithms are experimentally shown to have superior convergence properties over the classical IEKS.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
PublisherIEEE
Pages5875-5879
Number of pages5
ISBN (Electronic)9781509066315
DOIs
Publication statusPublished - May 2020
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech, and Signal Processing - Virtual conference, Barcelona, Spain
Duration: 4 May 20208 May 2020
Conference number: 45

Publication series

NameProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
PublisherIEEE
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing
Abbreviated titleICASSP
CountrySpain
CityBarcelona
Period04/05/202008/05/2020
OtherVirtual conference

Keywords

  • Extended Kalman smoother
  • Levenberg-Marquardt algorithm
  • Line search
  • Nonlinear estimation

Fingerprint Dive into the research topics of 'Levenberg-marquardt and line-search extended kalman smoothers'. Together they form a unique fingerprint.

Cite this