无人机
计算机科学
弹道
跟踪(教育)
实时计算
利用
基线(sea)
磁道(磁盘驱动器)
航程(航空)
运动(物理)
加速度
人工智能
模拟
工程类
计算机安全
航空航天工程
生物
遗传学
地质学
天文
教育学
经典力学
操作系统
海洋学
心理学
物理
作者
Federico Mason,Federico Chiariotti,Martina Capuzzo,Davide Magrin,Andréa Zanella,Michele Zorzi
标识
DOI:10.1109/infocomwkshps50562.2020.9162730
摘要
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.
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