With the development of networks such as mobile communications, Internet of Things (IoT), V2X (meaning Vehicle to everything, including Vehicle to Vehicle and Vehicle to Infrastructure), and Industrial Internet of Things (IIoT), the electromagnetic environment is becoming increasingly complex, illegal electronic devices are also increasing day by day, and there are severe coupling and intermodulation of various signals, which bring difficulties to the identification of leaked signal types. This paper proposes a leakage signal classification and recognition method based on fused features. Comprehensively utilizing high-dimensional feature extraction methods and graphical dimensionality reduction characterization methods, and combining with deep learning models such as residual networks and feature fusion analysis methods, the method can distinguish more comprehensively multiple types of electromagnetic leakage signals. The features method has with high robustness against noise and good interpretability, and can support the intelligent detection engineering application of radiation sources based on electromagnetic signal type recognition.