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Enhanced situation awareness for unmanned aerial vehicle operating in terminal areas with circuit flight rules

机译:通过巡回飞行规则增强了对在终端地区运行的无人机的态势感知能力

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摘要

This paper considers the situation awareness function associated with an unmanned aerial vehicle arriving at an uncontrolled airfield. Given no air traffic control service available within such a terminal area, the unmanned aerial vehicle needs to establish a good level of situation awareness by using its onboard sensors to detect and track other traffic aircraft. Comparing to the existing works which mainly use sensor observations in the filtering process, this paper exploits the circuit flight rules to provide extra knowledge about the target behaviour. This is achieved by using multiple models to describe the target motions in different flight phases and characterising the phase transition in a stochastic manner. Consequently, an interacting multiple model particle filter with state-dependent transition probabilities is developed to provide the required situation awareness function.
机译:本文考虑了与无人驾驶飞机到达不受控制的机场有关的态势感知功能。由于在这样的终端区域内没有空中交通管制服务,无人飞行器需要通过使用其机载传感器来检测和跟踪其他交通飞机来建立良好的态势感知水平。与在过滤过程中主要使用传感器观测结果的现有工作相比,本文利用电路飞行规则来提供有关目标行为的额外知识。这可以通过使用多个模型来描述不同飞行阶段中的目标运动并以随机方式表征相变来实现。因此,开发了具有状态依赖的转移概率的交互多模型粒子滤波器,以提供所需的态势感知功能。

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