Radar Signal Classification Based on Bayesian Optimized Support-vector Machine

Radar uses the scattering of electromagnetic waves to identify target coordinates and provide detection information. It plays a vital role in modern production and military affairs. How to classify and recognize radar signals is one of the main problems in current researches. With the emergence of various new radars, the demand for high accuracy in radar classification technology is gradually increasing. Furthermore, traditional signal classification methods cannot achieve good results. Aiming at the problems of low accuracy and poor performance of traditional classification methods, this paper proposes a radar signal classification technology based on Bayesian Optimized Support Vector Machines. The principle of the method is analyzed, and simulation data sets verify the theory. Moreover, the proposed method was compared with the traditional SVM, and the accuracy is increased by 10.71%.