Dual-Source Detection and Identification System Based on UAV Radio Frequency Signal

Abstract

With the rapid development of the technology industry, low, slow, and small civilian Unmanned aerial vehicle (UAV) have been popularized, bringing fun and convenience to life and work. However, with the popularization of UAV, all kinds of illegal flying behaviors have appeared successively, posing a threat to people's life and national security. To solve this problem, this article proposes a method and designs a system to detect and identify the UAV through the radio frequency (RF) signal emitted by the UAV itself. First, the RF front-end scans and intercepts the radio signals in the target airspace, then analyzes and identifies them by algorithms, and then implements the algorithm by field-programmable gate array (FPGA). Among them, algorithm recognition includes UAV flight control signal (FCS) detection and recognition, UAV image transmission signal (ITS) blind detection, and accurate recognition. Through the algorithm recognition result, it can be judged whether there are UAVs in the protected area. Finally, the hierarchical experimental verification method is used to demonstrate that the system can identify the number, type, and frequency band of UAVs in urban complex electromagnetic environment by using dual source detection and recognition algorithm, which provides a good foundation for UAV management and control.