In order to solve the problems of low accuracy and low robustness of specific emitter identification based on a single feature in complex electromagnetic environments,a method of specific emitter identification based on multi-feature fusion is proposed.This method takes the envelope of pulse front edges,the carrier frequency deviation and the harmonic distortion coefficient as the features,designs a multi-channel 1D convolutional neural network,and achieves the identification by fusing the features of different structures.The experiments show that this method has good accuracy even at a low SNR,and can effectively solve the problem of low accuracy of specific emitter identification based on a single feature in complex electromagnetic environments.