Modulation Recognition of Radar Signal Based on an Improved CNN Model
Jingjing Cai, Chao Li, Huanyin Zhang · 2019
In order to further improve the performance of radar signal modulation recognition, the radar signal modulation recognition algorithm based on an improved convolutional neural networks (CNN) model is proposed in this paper. As the CNN model has some shortcomings in the signal modulation recognition, such as long training time and poor generalization, the dense connection block layer and the global pooling layer are added in the CNN model to improve its performance. In the experiment, eight types of radar signals are used to verify the feasibility of the proposed algorithm, and the results show that the algorithm based on the improved CNN has the advantages of high recognition rate, short training time and good generalization.