文章基本信息

标题：Disturbance Estimation and Wave Filtering Using an Unscented Kalman Filter
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作者：Stefan Wirtensohn ; Stefan Wirtensohn ; Michael Schuster 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：23
页码：518-523
DOI：10.1016/j.ifacol.2016.10.488
语种：English
出版社：Elsevier
摘要：Abstract: 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.
关键词：Keywordsmotion estimationwave filteringUnscented Kalman Filtercorrelation analysis