Abstract: The rapid development of the unmanned aerial vehicle (UAV) industry has introduced security risks in low-altitude airspaces. To effectively control UAVs, a radio detection system that can identify UAV signals should be developed. To identify similar UAVs, this study proposes a UAV signal recognition method based on reclassification and separation of image transmission signals (ITSs) and flight control signals (FCSs). The pro-posed method extracts its time-domain parameters using the cyclic characteristics of the ITS and applies a classification decision tree to initially classify and identify the UAVs. Then, by separating the ITS and FCS, their time-frequency characteristic parameters are extracted, and finally, secondary classification is performed. Experimental results show

Key words: radio detection, orthogonal frequency division multiplexing (OFDM), segmented fast Fourier transform (FFT), time frequency analysis, feature extraction