Disturbance estimation and wave filtering using an unscented kalman filter

  • In this paper, utilisation of an Unscented Kalman Filter for concurrently performing disturbance estimation and wave filtering is investigated. Experimental results are provided that demonstrate very good performance subject to both tasks. For the filter, a dynamic model has been used which was optimised via correlation analysis in order to obtain a minimum set of relevant parameters. This model has also been validated by experiments deploying a small vessel. A simulation study is presented to evaluate the performance using known quantities. Experimental trials have been performed on the Rhine river. The results show that for instance flow direction and varying current velocities can continuously be estimated with decent precision, even while the boat is performing turning manoeuvres. Moreover, the filtering properties are very satisfactory. This makes the filter suitable for being used, for instance, in autonomous vessel applications or assistance systems.

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Metadaten
Author:Stefan Wirtensohn, Michael SchusterGND, Johannes ReuterORCiD
DOI:https://doi.org/10.1016/j.ifacol.2016.10.488
ISSN:2405-8963
Parent Title (English):10th Conference on Control Applications in Marine Systems (CAMS), 2016, Trondheim, Norway, 13-16 September 2016 (IFAC-PapersOnLine Vol. 49, Iss. 23)
Document Type:Conference Proceeding
Language:English
Year of Publication:2016
Release Date:2018/11/19
Tag:Correlation analysis; Motion estimation; Unscented Kalman Filter; Wave filtering
First Page:518
Last Page:523
Note:
Volltextzugriff für Angehörige der Hochschule Konstanz möglich.
Open Access?:Nein
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Licence (English):License LogoLizenzbedingungen Elsevier