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 degrees (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 degrees and elevation error of 7.7 degrees 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 degrees azimuth, 0-90 degrees 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.