A novel clustering-based filter for impulsive noise reduction in electromagnetic tomography (EMT)
A novel clustering-based filter for impulsive noise reduction in electromagnetic tomography (EMT)
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DOI：
10.1063/5.0018699
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发表时间：
2020-10
期刊：
影响因子：
1.6
通讯作者：
Ziqi Chen;Jorge R. Salas-Avila;Yang Tao;W. Yin;Zhijie Zhang
中科院分区：
文献类型：
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作者：
Ziqi Chen;Jorge R. Salas-Avila;Yang Tao;W. Yin;Zhijie Zhang
解调是电磁断层扫描 (EMT) 系统信号处理的关键步骤。 EMT 中会出现脉冲噪声，特别是当励磁电流从一个线圈切换到另一个线圈时。这主要是由于反电动势导致电流的不连续性产生电压尖峰。本文提出了一种新的基于聚类的方法，用于在卡尔曼滤波器解调的基础上减少这种脉冲噪声。卡尔曼滤波器能够对复用信号进行排斥性解调，但同时也会引入动态振荡。所提出的聚类方法能够成功地将信号与脉冲噪声分离并平滑解调后的动态振荡。仿真和实验结果表明，所提出的聚类方法可以将EMT测量的实部和虚部的信噪比提高20 dB以上。该技术在需要线圈切换的多通道线圈系统中也很有用。
Demodulation is a crucial step in signal processing for electromagnetic tomography (EMT) systems. Impulse noise appears in EMT, in particular, when excitation current is switched from one coil to another. This is mainly a result of the fact that the discontinuity of current creates voltage spikes due to back electromotive force. This paper proposes a novel clustering-based method for reducing this impulsive noise on the basis of Kalman filter demodulation. The Kalman filter is capable of demodulating the multiplexing signal reclusively, but it introduces dynamic oscillations at the same time. The proposed clustering method is able to successfully separate the signal from the impulse noise and smoothen the dynamic oscillations after demodulation. Simulation and experimental results show that the proposed clustering method can improve the signal-to-noise ratio by more than 20 dB in both the real and imaginary parts of EMT measurements. This technique is also useful in multi-channel coil systems where coil switching is necessary.