Research on radar target track recognition based on convolutional neural network

A large number of various radar signals in modern warfare make the electromagnetic environment more and more complex. It is urgent to quickly and accurately obtain the category information of the target track from a large number of radar data, and provide accurate and effective information for the battlefield command. The traditional radar-based target recognition method based on human experience or cognition is unable to effectively cope with the ever-changing battlefield and massive data. Based on the characteristics of actual radar data, this paper proposes a logarithmic preprocessing method and constructs a deep learning model based on convolutional neural network. The deep learning model realizes the recognition and detection of the target track in radar confrontation. The built model is tested based on the radar target track data generated by the simulation. Experiments show that the model can effectively detect and identify the target track.