论文标题
结合Lorawan和一个新的3D运动模型，用于远程无人机跟踪
Combining LoRaWAN and a New 3D Motion Model for Remote UAV Tracking
论文作者
论文摘要
在过去的几年中，无人驾驶汽车（UAV）的许多用途都吸引了科学和工业社区的兴趣。一个典型的情况在于在广泛的地理区域内使用无人机进行监视或目标搜索任务。在这种情况下，指挥中心的基础是通过利用其定期状态报告来准确估计和跟踪无人机的轨迹。在这项工作中，我们设计了一个临时跟踪系统，该系统利用远距离广泛区域网络（Lorawan）标准进行通信和恒定转弯速率和加速度（CTRA）运动模型的扩展版本来预测3D环境中的无人机运动。公开可用数据集中的仿真结果表明，我们的系统可以可靠地估计无人机的位置和轨迹，并且表现优于基线跟踪方法。
Over the last few years, the many uses of Unmanned Aerial Vehicles (UAVs) have captured the interest of both the scientific and the industrial communities. A typical scenario consists in the use of UAVs for surveillance or target-search missions over a wide geographical area. In this case, it is fundamental for the command center to accurately estimate and track the trajectories of the UAVs by exploiting their periodic state reports. In this work, we design an ad hoc tracking system that exploits the Long Range Wide Area Network (LoRaWAN) standard for communication and an extended version of the Constant Turn Rate and Acceleration (CTRA) motion model to predict drone movements in a 3D environment. Simulation results on a publicly available dataset show that our system can reliably estimate the position and trajectory of a UAV, significantly outperforming baseline tracking approaches.
