To deal with the problem of radar emitter recognition caused by parameter complexity and agility of muti-function radars in electronic intelligence reconnaissance field, a new recognition model based on deep restricted Boltzmann machine was proposed. The model was composed of multiple restricted Boltzmann machine. A bottom-up hierarchical unsupervised learning was used to obtain the initial parameters, and then the traditional back propagation algorithm was conducted to fine-tune the network parameters, and the Softmax was used to classify the results at last. Simulation and comparison experiment shows that the proposed method has the ability of extracting the parameter features and recognizing the radar emitters, and it has strong robustness as well as high recognition rate.