Drone Detection and Tracking Using RF Identification Signals

• Published in: Sensors (Basel, Switzerland) Switzerland), 2023-09, Vol.23 (17), p.7650
• Main Authors: Aouladhadj, Driss, Kpre, Ettien, Deniau, Virginie, Kharchouf, Aymane, Gransart, Christophe, Gaquière, Christophe
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; Altitude; Analysis; C-UAS; Classification; Communication; Computer Science; Computer software industry; detection system; drone; Drone ID; Drones; Engineering Sciences; Global positioning systems; GPS; Localization; Machine learning; Methods; Neural networks; Open source software; Performance evaluation; Radio frequency; RF signal; Safety and security measures; Semiconductor industry; Sensors; Signal processing; Software utilities; Surveillance; UAV; Unmanned aerial vehicles; Wavelet transforms
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23177650

The market for unmanned aerial systems (UASs) has grown considerably worldwide, but their ability to transmit sensitive information poses a threat to public safety. To counter these threats, authorities, and anti-drone organizations are ensuring that UASs comply with regulations, focusing on strategies to mitigate the risks associated with malicious drones. This study presents a technique for detecting drone models using identification (ID) tags in radio frequency (RF) signals, enabling the extraction of real-time telemetry data through the decoding of Drone ID packets. The system, implemented with a development board, facilitates efficient drone tracking. The results of a measurement campaign performance evaluation include maximum detection distances of 1.3 km for the Mavic Air, 1.5 km for the Mavic 3, and 3.7 km for the Mavic 2 Pro. The system accurately estimates a drone’s 2D position, altitude, and speed in real time. Thanks to the decoding of telemetry packets, the system demonstrates promising accuracy, with worst-case distances between estimated and actual drone positions of 35 m for the Mavic 2 Pro, 17 m for the Mavic Air, and 15 m for the Mavic 3. In addition, there is a relative error of 14% for altitude measurements and 7% for speed measurements. The reaction times calculated to secure a vulnerable site within a 200 m radius are 1.83 min (Mavic Air), 1.03 min (Mavic 3), and 2.92 min (Mavic 2 Pro). This system is proving effective in addressing emerging concerns about drone-related threats, helping to improve public safety and security.