Artificial neural networks in lightning location systems

Abstract

In this work, we introduce the use of self organizing Kohonen maps, a type of artificial neural network, for lightning electromagnetic waveform classification. We show how this natural classification can be used to discriminate lightning waveforms in a noisy environment. The utility and functionality of the proposed framework is confirmed by numerical results based on real lightning electric field waveforms from the lightning positioning and tracking system (LPATS) operated by the Swiss Telecom PTT.