Automatic recognition of radar signal types based on convolutional neural network

In the field of cognitive electronic warfare, automatic feature learning and recognition of radar signal is an important technology to ensure intelligence reconnaissance. This paper analyses the basic structure of convolutional neural network (CNN) and proposes an automatic recognition algorithm for radar signal. Firstly, the radar signal is transformed into time-frequency image, and the principal component information of the image is extracted by image processing method. Then, the designed network CNN-LeNet-5 is used to realize self-learning and recognition of features. The simulation results show that the algorithm can effectively identify eight kinds of radar signals in low signal-to-noise ratio.