Typical wideband EMI identification based on support vector machine

被引：1
|
作者：
Zhu F. [1 ]
Jiang Q. [1 ]
Lin C. [1 ]
Yang X. [1 ]
机构：
[1] School of Electrical Engineering, Southwest Jiaotong University, Chengdu
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2021年 / 43卷 / 09期
关键词：
Electromagnetic interference (EMI); Feature extraction; Signal processing; Support vector machine (SVM);
D O I：
10.12305/j.issn.1001-506X.2021.09.04
中图分类号：
学科分类号：
摘要：
Due to the complex electromagnetic environment around civil aviation, once the electromagnetic interference (EMI) is produced, it is not easy to be investigated, especially the random strong wideband interference. For wideband, an interference source recognition method based on support vector machine (SVM) is proposed. By measuring the spectral data of the signal in real time and analyzing its characteristics, five features of the evenlope factor, energy, peak value, mean and variance are selected as feature vectors, and principal component analysis is used to reduce data redundancy, finally, the type of the interference source is determined by SVM. Simulation results show that the identification algorithm proposed in this paper can effectively identify 6 types of wideband interference, and the identification accuracy is up to 98.33%. © 2021, Editorial Office of Systems Engineering and Electronics. All right reserved.
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收藏
页码：2400 / 2406
页数：6
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