Design of a counter-drone visualisation platform incorporating sensor-data fusion

This paper describes the development of a counter-unmanned aircraft system (C-UAS) platform for sensor-data fusion and visualisation. The report outlines the design, implementation and integration of sensor inputs for the effective detection, identification and tracking (DTI) of both cooperative and noncooperative unmanned aircraft, commonly known as drones, in airspace. With a focus on the direct remote identification sensing, the platform architecture is based on cutting-edge web platform technologies to create a modern prototype. The objective is to develop a prototype solution that can be extended to deploy and test more sophisticated sensor-data fusion algorithms on real-time data for C-UAS. A first version of a sensor-data fusion algorithm is implemented for data from direct remote identification (DRI) sensors using dynamic time warping (DTW). The Python implementation of DTW is discussed, highlighting its efficiency and applicability in real-time operations. A frontend interface of the platform is provided, offering a user-friendly graphical user interface for monitoring and controlling DTI drone activity. Providing a full-stack solution utilizing open-source tools for data handling, processing, and visualisation. The frontend application incorporates the visualisation of the official geo-zones. Future developments are discussed, such as implementing geo-zoning and geo-fencing alerts.

LAGARAS Stylianos;  AMENDOLA Danilo;  ANDERSON David; 

2025-02-26

IEEE

JRC139000

978-3-903176-68-3 (online),    979-8-3315-4245-0,   

2473-3644 (online),   

https://ieeexplore.ieee.org/document/10767076,    https://publications.jrc.ec.europa.eu/repository/handle/JRC139000,   

10.52545/3-2 (online),