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Interval Kalman filtering in navigation system design for an uninhabited surface vehicle

机译:无人水面航行器导航系统设计中的区间卡尔曼滤波

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摘要

This paper reports on the potential application of interval Kalman filtering techniques in the design of a navigation system for an uninhabited surface vehicle named Springer. The interval Kalman filter (IKF) is investigated for this task since it has had limited exposure for such usage. A state-space model of the Springer steering dynamics is used to provide a framework for the application of the Kalman filter (KF) and IKF algorithms for estimating the heading angle of the vessel under erroneous modelling assumptions. Simulations reveal several characteristics of the IKF, which are then discussed, and a review of the work undertaken to date presented and explained in the light of these characteristics, with suggestions on potential future improvements. © The Royal Institute of Navigation 2013.
机译:本文报告了区间卡尔曼滤波技术在无人驾驶水上运输工具Springer导航系统设计中的潜在应用。为此,对间隔卡尔曼滤波器(IKF)进行了研究,因为它在此类用途中的暴露程度有限。使用Springer转向动力学的状态空间模型为卡尔曼滤波器(KF)和IKF算法的应用提供框架,以在错误的建模假设下估算船舶的航向角。模拟显示了IKF的几个特征,然后对其进行了讨论,并根据这些特征对迄今为止进行的工作进行了介绍和解释,并提出了未来可能的改进建议。 ©皇家航海学院,2013年。

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