Remote Tracking of UAV Swarms via 3D Mobility Models and LoRaWAN Communications

Federico Mason, Martina Capuzzo, Davide Magrin, Federico Chiariotti, Andrea Zanella, Michele Zorzi

Research output: Contribution to journalJournal articleResearchpeer-review

2 Citations (Scopus)


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. We analyze the trade-off in setting the main parameters of the communication system and Adaptive Data Rate (ADR) scheme, showing how our tracking system can handle large swarms of drones at distances up to 4 km. Simulation results on a publicly available dataset show that our system can reliably estimate the position and trajectory of a swarm of UAVs, significantly outperforming baseline tracking approaches.

Original languageEnglish
JournalI E E E Transactions on Wireless Communications
Issue number5
Pages (from-to)2953-2968
Number of pages16
Publication statusPublished - 1 May 2022


  • Adaptation models
  • Drones
  • Mathematical models
  • Solid modeling
  • Three-dimensional displays
  • Tracking
  • Wireless communication
  • Internet of Things (IoT)
  • motion estimation
  • Unmanned aerial vehicles (UAVs)
  • position measurement


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