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

摘要/Abstract

摘要：

由于民航周围电磁环境复杂, 一旦产生电磁干扰(electromagnetic interference，EMI), 就不易被排查, 特别是随机性较强的宽带干扰。对此, 提出一种基于支持向量机(support vector machine, SVM)的干扰源识别方法。通过实时测量干扰信号的频谱数据, 并分析其特点, 选择包络因子、频谱能量、频谱峰值、均值和方差5个特征向量, 用主成分分析法降低数据冗余程度, 最后采用SVM来判断干扰源类型。仿真结果证明, 所提算法能有效识别6类典型机场宽带干扰源, 识别精度可达98.33%。

关键词: 电磁干扰, 信号处理, 特征提取, 支持向量机

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)

中图分类号:

V243.1

朱峰, 蒋倩倩, 林川, 杨啸. 基于支持向量机的典型宽带电磁干扰源识别[J]. 系统工程与电子技术, 2021, 43(9): 2400-2406.

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.

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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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