A new method of electromagnetic radiant sources based on support vector machine
Yang Sun, Xinyuan Hu, Shoulin Yin, Jie Liu · 2016
Traditional distinction and recognition methods of electromagnetic radiation source have some shortcomings with highly error and long time. Therefore, Wilson algorithm, Lee algorithm and near field wave impedance theory have been proposed to analyze radiation source characteristics. And it presented common-mode radiation noise testing method of poor-average algorithm and differential mode noise testing method of variance algorithm respectively according to the different radiation source characteristics. Nevertheless, there are still some questions with imprecise location. By acquiring electric field intensity distribution around space of electromagnetic radiation sources, we can determine the direction characteristics of the radiation sources. Using the directional characteristic parameter with high differentiation degree, we make accurate classification and recognition for electromagnetic radiation sources based on support vector machine (SVM). In this paper, we analyze three basic antenna radiation models. It establishes cube reception array to obtain its filed strength value of far zone field in the same position, in addition, it adopts support vector machine method to deal with data and sets up a evaluation model to analyze recognition accuracy. Finally, experimental results show that the proposed method has high recognition accuracy. What's more, we illustrate the new scheme from three aspects with anti-noise performance, data normalization method and F1 value.