Two-Dimensional Real-Time Direction-Finding System for UAV RF Signals Based on Uniform Circular Array and MUSIC-WAA
Jizan Zhu, Kuangang Fan, Qing He, Jingzhen Ye, Aigen Fan · Drones · 2025
To address the growing security risks posed by unauthorized unmanned aerial vehicle (UAV) activities, this paper proposes a real-time two-dimensional direction-finding (DF) system for UAVs based on radio frequency (RF) signals. This system employs a six-element uniform circular array (UCA), synchronized HackRF One receivers, and a hybrid algorithm integrating the multiple signal classification (MUSIC) method with a novel weighted average algorithm (WAA). By optimizing the MUSIC spectrum search process, the WAA reduces the computational complexity by over 99.9% at a resolution of 0.1° (from 3,240,000 to 1200 spectral function calculations), enabling real-time estimation of the azimuth and elevation angles. The experimental results demonstrate an average azimuth error of 7.0° and elevation error of 7.7° for UAV hovering distances of 30–200 m and heights of 20–90 m. Real-time flight tracking further validates the system’s dynamic monitoring capabilities. The hardware platform, featuring omnidirectional coverage (0–360° azimuth, 0–90° elevation) and dual-band operation (2.4 GHz/5.8 GHz), offers scalability and cost-effectiveness for low-altitude security applications. Despite limitations in the elevation sensitivity due to the UCA’s geometry, this work establishes a practical foundation for UAV monitoring, emphasizing computational efficiency, real-time performance, and adaptability to dynamic environments.