Aiming at the problem that the radio frequency fingerprint(RFF) extracted by convolutional neural network(CNN) is easily interfered by the channel fingerprint, resulting in a sharp decrease in recognition accuracy. An IEEE80211a signal radiation source identification method with channel fingerprint removal was proposed. Firstly, extract the timedomain training sequence of the frame head of the signal to be recognized, and the timedomain training sequence is used as the reference signal. Then use the LMS adaptive filter and timedomain training sequence for channel equalization and compensation. Finally, IQCNet model is used to extract the RFF from the time domain signal for device identification. The experimental results show that the recognition rate of 6 wireless routers based on IEEE80211a protocol reaches up to 96% in different wireless channel environments. The proposed method can effectively remove the negative influence of channel fingerprint on RFF identification.