In order to enable the deep neural networks to accurately identify the emitters of different transmission channels, a domain-adaptation specific emitter identification method based on deep residual shrinkage network (DRSN) fusion Transformer encoder was proposed. DRSN was used to automatically remove the noise from the I/Q received signals through the soft threshold module, and the Transformer encoder was used to further extract the dependent features among symbols in the signals. The domain-adaptation adversarial learning method was used to map target signals from different domains to target features with the same distribution, which enabled the DRSN-Transformer encoder network model to accurately extract the radio frequency fingerprint （RFF） features independent of the channel domain, and to realize the accurate identification of the emitter in the target domain under channel changes. The modulator distortion signal model was used for simulation experiments. The results show that compared with the ResNet model and the DRSN model, the average recognition accuracy of the model in this paper has increased by 2.98 percentage points and 1.65 percentage points respectively. The domain-adaptation adversarial learning method based on DRSN-Transformer encoder network model can effectively reduce the inconsistency of signal feature distribution between the source domain and the target domain, compared with DRSN-Transformer encoder network model trained by traditional methods, the recognition accuracy is increased by 20.73 percentage points at a signal-to-noise ratio of 27 dB, which significantly improves the identification performance when the channel changes. Compared with the traditional learning methods, although the proposed method adds the adversarial training process of the feature extraction network and the domain discrimination network, the final trained feature extraction network can accurately extract fingerprint features that are independent of channel changes, and has certain application value in the specific emitter identification.