首页> 外文期刊>Journal of Intelligent & Robotic Systems: Theory & Application >Tracking of Ocean Surface Objects from Unmanned Aerial Vehicles with a Pan/Tilt Unit using a Thermal Camera
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Tracking of Ocean Surface Objects from Unmanned Aerial Vehicles with a Pan/Tilt Unit using a Thermal Camera

机译:使用热量相机跟踪无人驾驶空中车辆的海面对象

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This paper presents four vision-based tracking system architectures for marine surface objects using a fixed-wing unmanned aerial vehicle (UAV) with a thermal camera mounted in a pan/tilt gimbal. The tracking systems estimate the position and velocity of an object in the North-East (NE) plane, and differ in how the measurement models are defined. The first tracking system measures the position and velocity of the target with georeferencing and optical flow. The states are estimated in a Kalman filter. A Kalman filter is also utilized in the second architecture, but only the georeferenced position is used as a measurement. A bearing-only measurement model is the basis for the third tracking system, and because the measurement model is nonlinear, an extended Kalman filter is used for state estimation. The fourth tracking system extends the bearing-only tracking system to let navigation uncertainty in the UAV position affect the target estimates in a Schmidt-Kalman filter. All tracking architectures are evaluated on data gathered at a flight experiment near the Azores islands outside of Portugal. The results show that various marine vessels can be tracked quite accurately.
机译:本文介绍了使用固定翼无人驾驶车辆(UAV)的海面对象的四个基于视觉的跟踪系统架构,其中包含在平移/倾斜万向节中安装的热摄像头。跟踪系统估计了东北(NE)平面中对象的位置和速度,以及如何定义测量模型的不同。第一跟踪系统测量目标的位置和速度与地质传播和光学流动。这些国家估计在卡尔曼滤波器中。卡尔曼滤波器也用于第二架构中,但仅使用地理位置的位置作为测量。仅辅助测量模型是第三跟踪系统的基础,因为测量模型是非线性的,所以扩展的卡尔曼滤波器用于状态估计。第四跟踪系统扩展了仅辅助跟踪系统,让UAV位置中的导航不确定性影响施密特-Kalman滤波器中的目标估计。所有跟踪架构都是在葡萄牙境外亚速尔群岛岛附近的飞行试验中收集的数据。结果表明,可以非常准确地跟踪各种海洋船只。

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