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Disturbance Estimation and Wave Filtering Using an Unscented Kalman Filter

机译:使用Unscented Kalman滤波器的干扰估计和波过滤

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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.
机译:在本文中,研究了未激活的卡尔曼滤波器用于同时执行干扰估计和波滤波的利用。提供了实验结果,表明对两项任务进行了非常好的性能。对于滤波器,已经使用动态模型,其通过相关分析优化,以便获得最小的相关参数集。该模型也通过部署小船只的实验验证。提出了一种使用已知量来评估性能的仿真研究。在莱茵河上进行了实验试验。结果表明,例如流动方向和不同的电流速度可以连续地用体面的精度估计,即使船在船上正在进行转动的操纵时也能估计。此外,过滤性质非常令人满意。这使得用于例如在自动血管应用或辅助系统中使用的过滤器。

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