With the increasingly complex electromagnetic environment, wireless communication is facing severe challenges, making modulation recognition of electromagnetic signals, which becomes an important aspect of cognitive radio technology. Deep learning techniques have poor interpretability and little applicability, while traditional identification techniques have limited representation capabilities. In this paper, we propose an intelligent modulation recognition method that combines the advantages of both methods by embedding domain knowledge. In order to enhance classification performance and network interpretability, this technique integrates deep neural networks with high-order information and electromagnetic signal spectrum processes. Based on the RML2018 dataset, our method achieves a 6.31% improvement in modulation recognition accuracy compared to the ResNet method.