  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.
