In order to solve the problem of the different distribution between the testing samples and training samples, this paper proposes a modulation recognition method based on the domain adaptive neural network. Firstly, VGG 16 deep convoluted neural network is utilized for extracting the features of wavelet transform images.Then the high dimensional features are reduced by using the autoencoder, and the CORAL losses between training samples and testing samples are calculated.Finally, the optimal classification loss and the CORAL loss are combined to optimize the model.The simulation results show that under condition of different signal categories or different channel environments, the recognition accuracy of signals tested can be improved more than 5% by introducing domain adaptation technology.