Abstract
A single-site lightning electromagnetic pulse (LEMP) localization approach based on deep learning was proposed and practiced. The approach was based on a large amount of ground-based lightning location and waveform data in the VLF/LF frequency band. A model for predicting the propagation distance of LEMP based on a deep learning method was proposed. The model used multiple types of LEMP waveform data as well as location data for parameter learning. The new model for detecting lightning activity has been validated against ADTD systems. The verification results for thunderstorms in the range of 1000 km show that the relative error of the model for the prediction of signal propagation distance was 2.75–13.08%. Affected by the azimuth calculation error, the relative error of single-site geolocation was 4.91–15.26%.
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