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. (C) 2016, IFAC (International Federation Automatic Control) Hosting by Elsevier Ltd. All rights reserved.