Mostajabi Amirhossein, Karami Hamidreza, Azadifar Mohammad, Ghasemi Alireza, Rubinstein Marcos, Rachidi Farhad
Electromagnetic Compatibility Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Institute for Information and Communication Technologies, University of Applied Sciences of Western Switzerland (HES-SO), Yverdon-les-Bains, Switzerland.
Sci Rep. 2019 Nov 22;9(1):17372. doi: 10.1038/s41598-019-53934-4.
Electromagnetic Time Reversal (EMTR) has been used to locate different types of electromagnetic sources. We propose a novel technique based on the combination of EMTR and Machine Learning (ML) for source localization. We show for the first time that ML techniques can be used in conjunction with EMTR to reduce the required number of sensors to only one for the localization of electromagnetic sources in the presence of scatterers. In the EMTR part, we use 2D-FDTD method to generate 2D profiles of the vertical electric field as RGB images. Next, in the ML part, we take advantage of transfer learning techniques by using the pretrained VGG-19 Convolutional Neural Network (CNN) as the feature extractor tool. To the best of our knowledge, this is the first time that the knowledge of pretrained CNNs is applied to simulation-generated images. We demonstrate the skill of the developed methodology in localizing two kinds of electromagnetic sources, namely RF sources with a bandwidth of 0.1-10 MHz and lightning impulses. For the localization of lightning, based on the experimental recordings in the Säntis region, the new approach enables accurate 2D lightning localization using only one sensor, as opposed to current lightning location systems that need at least two sensors to operate.
电磁时间反转（EMTR）已被用于定位不同类型的电磁源。我们提出了一种基于电磁时间反转和机器学习（ML）相结合的新型源定位技术。我们首次表明，在存在散射体的情况下，机器学习技术可与电磁时间反转结合使用，将电磁源定位所需的传感器数量减少至仅一个。在电磁时间反转部分，我们使用二维有限时域差分（2D-FDTD）方法生成垂直电场的二维剖面图作为RGB图像。接下来，在机器学习部分，我们利用迁移学习技术，使用预训练的VGG-19卷积神经网络（CNN）作为特征提取工具。据我们所知，这是首次将预训练的卷积神经网络知识应用于模拟生成的图像。我们展示了所开发方法在定位两种电磁源方面的能力，即带宽为0.1 - 10 MHz的射频源和雷电脉冲。对于雷电定位，基于在圣蒂斯地区的实验记录，与当前至少需要两个传感器才能运行的雷电定位系统不同，新方法仅使用一个传感器就能实现精确的二维雷电定位。
