In response to the problem of low accuracy in individual identification of communication radiation sources under channel noise interference, a communication radiation source individual identification method that integrates time-frequency characteristics is proposed by utilizing the difference in channel noise interference suppression effect of signal mapping to different time-frequency domains. Firstly, extract I/Q, power spectrum, and wavelet spectrum information from the radiation source signal, and fuse the time-frequency information of the signal through one-dimensional convolution in both horizontal and vertical directions; Then, the channel attention module and spatial attention module are used to fuse time-frequency features; Finally, M-ResNeXt network is used to achieve individual identification of radiation sources under channel noise interference. The experimental results show that under the interference of three channel noises, Gaussian white noise with a signal-to-noise ratio (SNR) of 15dB, Rayleigh, and Rician, the recognition accuracy of the proposed time-frequency feature fusion method reaches 97.6%, 97.7%, and 98.5% respectively. Even when facing unknown noise interference at an SNR of 15dB, it can still achieve a recognition accuracy of over 97.7%. Therefore, the time-frequency feature fusion method can significantly improve the accuracy and robustness of individual communication radiation source identification.