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A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle

机译:用于无人水面飞行器制导与控制的集成鲁棒导航技术

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This paper proposes the novel use of a weighted Interval Kalman Filter (wIKF) in a robust navigational approach for integration with the guidance and control systems of an uninhabited surface vehicle named Springer. The waypoint tracking capability of this technique is compared with that of one that uses a conventional Kalman Filter (KF) navigational design, when the model of the sensing equipment used by the filter is incorrect. In this case, the KF fails to predict correctly the vehicle's heading, which consequently impacts negatively on the performance of its integrated navigation, guidance and control (NGC). However, the use of a wIKF technique that is immune to this kind of erroneous modelling endows the integrated NGC system with better accuracy and efficiency in completing a mission.
机译:本文提出了一种加权区间卡尔曼滤波器(wIKF)在一种稳健的导航方法中的新颖用法,该方法可与名为Springer的无人水面飞行器的制导和控制系统集成。当该技术使用的传感设备的模型不正确时,将该技术的航点跟踪能力与使用常规卡尔曼滤波器(KF)导航设计的航点跟踪能力进行比较。在这种情况下,KF无法正确预测车辆的前进方向,因此会对其集成导航,制导和控制(NGC)的性能产生负面影响。但是,不受这种错误建模影响的wIKF技术的使用使集成NGC系统在完成任务时具有更高的准确性和效率。

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