A UAV localization method based on RF TDOA and visual YOLO feature fusion

Abstract In recent years, the rapid development of UAV technology has opened up a wide range of application prospects, but unauthorized UAV flights pose potential threats to low-altitude airspace security. Existing monitoring methods often rely on expensive high-precision equipment or single-sensor systems, making it difficult to achieve low-cost yet high-accuracy UAV localization and identification. A localization method based on a multi-sensor fusion strategy combining RF and visual data, that is, integrating RF TDOA localization technology with lightweight YOLO visual localization technology (TAYT, TDOA, and YOLO technology) is proposed in this paper. The method isolates the radio frequency bands used by the UAV, discovers the UAV through RF TDOA frequency scanning positioning, and combines Yolo images to locate the UAV. Experimental results demonstrate that this approach overcomes issues such as large errors caused by the susceptibility of spectrum sensors to environmental noise interference and non-line-of-sight effects. The minimum error of the positioning error is about 2.79 meters compared to the reference standard. A low-cost and high-efficiency positioning technology for effective low-altitude UAV monitoring is provided in this paper.