Research on the Radar Signal Classification Method Based on the Deep Faith Network Model

Abstract

In the development of machine learning, deep learning, as a research content that researchers focus on, has a relatively strong ability to represent data. Its core basis is to build a neural network with multi-hidden layer structure and a large number of data, so as to obtain the features contained in the data and improve the accuracy of classification prediction. Radar signal classification is an important technology for radar signal processing. After the emergence of a new radar system, the application advantages of traditional signal classification methods are becoming less and less. However, combined with deep learning, signal classification can be optimized on the basis of automatic learning of data characteristics. Therefore, on the basis of understanding the current research status of signal classification in radar countermeasures, this paper conducts in-depth research on the technical concept of deep learning, and thus proposes a radar signal classification method based on deep belief and network model.