基于支持向量机的典型宽带电磁干扰源识别

doi:10.12305/j.issn.1001-506X.2021.09.04

Abstract

Abstract:

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%.

Key words: electromagnetic interference (EMI), signal processing, feature extraction, support vector machine (SVM)

CLC Number:

V243.1

Feng ZHU, Qianqian JIANG, Chuan LIN, Xiao YANG. Typical wideband EMI identification based on support vector machine[J]. Systems Engineering and Electronics, 2021, 43(9): 2400-2406.

Figures/Tables 10

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名称	型号	功能
LED路灯	HC-BLZM	民用照明灯泡
大功率投光灯	EF1KO1SSMGR	机场照明灯泡
机场卤素灯	58304	机场跑道灯泡

仪器名称	型号	频率范围
频谱仪	N9340B	9 kHz~3 GHz
频谱分析仪	N9010B EXA	10 Hz~44 GHz
对数周期天线	DS3200	30 MHz~2 GHz
双锥天线	HK116	20~300 MHz

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Typical wideband EMI identification based on support vector machine

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