YOLOv5-based complex typical communication signal rapid identification and classification method

The invention provides a YOLOv5-based complex typical communication signal rapid identification and classification method, which is characterized in that complex typical communication signals are converted into a time-frequency graph by using SPWVD time-frequency analysis, the complex typical communication signals comprise single carrier frequency signals, frequency hopping signals and linear frequency sweeping signals, and the time-frequency graph is predicted and classified by using a YOLOv5 network. A YOLOv5 network structure is improved aiming at the problems of rapid conversion of signal categories and huge data volume, only medium and small target detection heads are reserved, and detection is performed in combination with a SIoUloss loss function and non-maximum suppression, so that the network parameter quantity is reduced and the recognition speed is improved while the network accurately recognizes various communication signal categories, and the method is suitable for large-scale popularization and