A Novel Radar Signal Recognition Method based on Deep Learning

摘要

Radar signal recognition is of great importance in the field of electronic intelligence reconnaissance. To deal with the problem of parameter complexity and agility of multi-function radars in radar signal recognition, a new model called radar signal recognition based on deep restricted Boltzmann machine (RSRDRBM) is proposed to extract the feature parameters and recognize the radar emitter. This model is composed of multiple restricted Boltzmann machine. A bottom-up hierarchical unsupervised learning is used to obtain the initial parameters, and then the traditional BP algorithm is conducted to fine-tune the network parameters, softmax is used to classify the results at last. Simulation and comparison experiment show 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 correct recognition rate.