To solve the problem of insufficient identification performance in the research of intelligent individual radar emitter identification by using traditional convolutional neural network in low signal-to-noise ratio environment,a method of individual radar emitter identification based on Short-Time Fourier Transform (STFT) and EfficientNet is proposed.Firstly,the STFT is applied to the radar signal to extract time-frequency features,and then multiple MBconv modules in the EfficientNet are used to superimpose different time-frequency feature images to mine the more complex and abstract deep-level time-frequency features hidden in the signal image,including the distribution of signal intensity,time-frequency mode,periodic changesetc.,to complete individual classification and identification.Three parameters of network depth,width and image resolution of the EfficientNet can be simultaneously changed,which solves the problems of gradient disappearance and gradient explosion.The experimental results show that,in low signal-to-noise ratio environment,the method of individual radar emitter identification based on STFT and EfficientNet has better identification performance than traditional convolutional neural network.