A study on the implementation of nonlinear Kalman filter applying MMG model

Koike, Hiroaki; Dostal, Leo; Sawada, Ryohei; Miyauchi, Yoshiki; Maki, Atsuo

doi:https://doi.org/10.1007/s00773-023-00953-6

A study on the implementation of nonlinear Kalman filter applying MMG model

Koike, Hiroaki; Dostal, Leo; Sawada, Ryohei et al.

Journal of Marine Science and Technology (Japan), 2023, 28(4), 733-745

アクセス数:310件（2025-07-26 22:16 集計）

固定URL: https://hdl.handle.net/11094/93290

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タイトル	A study on the implementation of nonlinear Kalman filter applying MMG model
著者	著者名 Koike, Hiroaki
	著者名 Dostal, Leo
	NRID 1000000825911 1000000825911 著者名 Sawada, Ryohei
	著者名 Miyauchi, Yoshiki
	NRID 1000050556496 1000050556496 ORCID 0000-0002-2819-1297 0000-0002-2819-1297 researchmap permalink atsuo_maki atsuo_maki Scopus Author ID 24503751100 24503751100 著者名 Maki, Atsuo
キーワード等	EnKF
	Kalman filter
	MMG model
	State estimation
	UKF
内容	The version of record of this article, first published in Journal of Marine Science and Technology (Japan), is available online at Publisher’s website: https://doi.org/10.1007/s00773-023-00953-6
抄録	Many technologies need to be established to realize autonomous ships. In particular, accurate state estimation in real time is one of the most important technologies. In the ship and ocean engineering fields, there have been many studies on state estimation using nonlinear Kalman filters. Several methods have been proposed for nonlinear Kalman filters. However, there is insufficient verification on the selection of which filter should be applied among them. Therefore, this study aims to validate the filter selection to provide a guideline for filter selection. The effects of modeling error, observation noise, and type of maneuvers on the estimation accuracy of the unscented Kalman filter (UKF) and ensemble Kalman filter (EnKF) used in this study were investigated. In addition, it was verified whether filtering could be performed in real time. The results show that modeling error significantly impacts the estimation accuracy of the UKF and EnKF. However, the observation noise and types of maneuvers did not have an impact like the modeling error. Thus, we obtained the guideline that UKF and EnKF should be used differently depending on the required computation time. We also obtained that keeping the modeling error sufficiently small is essential to improving the estimation accuracy.
出版者	Springer
収録物名	Journal of Marine Science and Technology (Japan)
巻(号)	28(4)
ページ	733-745
刊行年月	2023-10-28
言語	英語
ハンドルURL	https://hdl.handle.net/11094/93290
PISSN	09484280
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.1007/s00773-023-00953-6
アクセス権	open access
権利情報	This article is licensed under a Creative Commons Attribution 4.0 International License.
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCMI資源タイプ	text
DCTERMS.bibliographicCitation	Journal of Marine Science and Technology (Japan). 2023, 28(4), p. 733-745
DC.title	A study on the implementation of nonlinear Kalman filter applying MMG model
DC.creator	Koike, Hiroaki
	Dostal, Leo
	Sawada, Ryohei
	Miyauchi, Yoshiki
	Maki, Atsuo
DC.publisher	Springer
DC.language' scheme='DCTERMS.RFC1766	英語
DC.type' scheme='DCTERMS.DCMIType	text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2023-10-28
DC.identifier	https://doi.org/10.1007/s00773-023-00953-6
DC.subject	EnKF
	Kalman filter
	MMG model
	State estimation
	UKF
DC.description	The version of record of this article, first published in Journal of Marine Science and Technology (Japan), is available online at Publisher’s website: https://doi.org/10.1007/s00773-023-00953-6
DCTERMS.abstract	Many technologies need to be established to realize autonomous ships. In particular, accurate state estimation in real time is one of the most important technologies. In the ship and ocean engineering fields, there have been many studies on state estimation using nonlinear Kalman filters. Several methods have been proposed for nonlinear Kalman filters. However, there is insufficient verification on the selection of which filter should be applied among them. Therefore, this study aims to validate the filter selection to provide a guideline for filter selection. The effects of modeling error, observation noise, and type of maneuvers on the estimation accuracy of the unscented Kalman filter (UKF) and ensemble Kalman filter (EnKF) used in this study were investigated. In addition, it was verified whether filtering could be performed in real time. The results show that modeling error significantly impacts the estimation accuracy of the UKF and EnKF. However, the observation noise and types of maneuvers did not have an impact like the modeling error. Thus, we obtained the guideline that UKF and EnKF should be used differently depending on the required computation time. We also obtained that keeping the modeling error sufficiently small is essential to improving the estimation accuracy.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	93290
citation_title	A study on the implementation of nonlinear Kalman filter applying MMG model
citation_author	Koike, Hiroaki
	Dostal, Leo
	Sawada, Ryohei
	Miyauchi, Yoshiki
	Maki, Atsuo
citation_publisher	Springer
citation_language	英語
citation_date	2023-10-28
citation_journal_title	Journal of Marine Science and Technology (Japan)
citation_volume	28
citation_issue	4
citation_firstpage	733
citation_lastpage	745
citation_doi	https://doi.org/10.1007/s00773-023-00953-6
citation_public_url	https://hdl.handle.net/11094/93290

A study on the implementation of nonlinear Kalman filter applying MMG model

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