Report/publication
Unmanned Aircraft Systems
2024
- Abstract
- This technical report describes the development of a counter-unmanned aerial system (C-UAS) platform for sensor-data fusion and visualisation. The report outlines the design, implementation and integration of sensor inputs for the effective identification and tracking of both cooperative and non-cooperative drones in airspace. With a focus on the direct remote identification sensing, the platform architecture is based on trending technologies, i.e., message broker, Python data processing backend, and Redis in-memory database. The objective of the platform is to become a base platform which can be extended to deploy and test more sophisticated sensor-data fusion algorithms on real-time data. A first version of a sensor-data fusion algorithm is implemented for direct remote identification sensors. To this end, dynamic time warping (DTW) is used to fuse 3D trajectories of sensor data, even if the time series data are not synchronised in the time domain. Additionally, the frontend interface of the platform is described, offering a user-friendly graphical user interface for monitoring and controlling drone activity. The work concludes with the successful creation of a full-stack infrastructure utilizing open-source tools for data handling, processing, and visualization. The frontend application incorporates the visualisation of the official Belgian geo-zones, and future developments are discussed, such as implementing geo-zoning and geo-fencing alerts.
- Authors
- LAGARAS Stylianos; AMENDOLA Danilo; ANDERSON David;
- Year
- 2024
- Publisher
- Publications Office of the European Union
- Citation
Lagaras, S., Amendola, D. and Anderson, D., A counter-drone visualisation platform incorporating sensor-data fusion, Publications Office of the European Union, Luxembourg, 2024, doi:10.2760/560445, JRC137155. - Identifiers
JRC JRC137155 ISBN 978-92-68-18339-7 (online) ISSN 1831-9424 (online) DOI 10.2760/560445 - Download file
- A counter-drone visualisation platform incorporating sensor-data fusion
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