Detection, Tracking, and Identification of Drones: an Overview on Counter-UAS Techniques, and Open Challenges

Abstract

With the proliferation of Unmanned Aircraft Systems (UASs), a broad spectrum of legitimate, nuisance, and malicious applications has introduced new challenges for airspace management. A large number of UASs available on the market, and UASs can also be homemade (including being 3D printed), further complicating detection and classification efforts. Traditional traffic control and surveillance systems are facing disruption from UASs proliferation, which enable innovative use cases across various sectors, such as precision agriculture and infrastructure inspection, but also create opportunities for misuse, such as illegal surveillance and contraband delivery. In this evolving landscape, C-UAS technology has emerged as a crucial tool to mitigate the growing risks associated with unauthorized drone usage. To this end, it is critical to understand the capability, limitations and challenges associated to C-UAS research and development efforts related to detection, tracking, and identification of unauthorized UASs in public and critical infrastructures. Given the diverse range of sensors employed in C-UAS systems, such as radar, radiofrequency, electro-optical, and acoustic sensors, and the heterogeneous nature of UASs, this study emphasizes the importance of multi-sensor data fusion to achieve accurate DTI in real-time. The integration of different sensors is key to enhancing system reliability and addressing the complexities of modern airspace. Furthermore, new models and algorithms are necessary to improve target tracking capabilities for UASs. The study presents a taxonomy of sensors used in C-UAS and highlights the need for a comprehensive, integrated approach. It also delves into the challenges of implementing a multi sensor data fusion algorithm, providing a model for sensor fusion in DTI, along with an overview of the current literature and available commercial solutions. By adopting a holistic approach, this study aims to contribute to the advancement of robust, reliable C-UAS systems that can effectively manage the rising threat of unauthorized UASs.

Cite this work

@inproceedings{grieco2025detection,
  title = {{Detection, Tracking, and Identification of Drones: an Overview on Counter-UAS Techniques, and Open Challenges}},
  author = {Giovanni Grieco and Danilo Amendola and D. Chris Anderson},
  booktitle = {2025 Integrated Communications, Navigation and Surveillance Conference (ICNS)},
  year = {2025},
  doi = {10.1109/icns65417.2025.10976862},
  url = {https://doi.org/10.1109/icns65417.2025.10976862}
}

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