Lightning Mapping: Techniques, Challenges, and Opportunities
| Autor: | Ammar Ahmed Alkahtani, Mona Riza Mohd Esa, Zen Kawasaki, Ammar Alammari, Sieh Kiong Tiong, Mohd Riduan Ahmad, Fuad Noman |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Signal Processing (eess.SP)
010504 meteorology & atmospheric sciences General Computer Science 02 engineering and technology computer.software_genre 01 natural sciences Time of arrival 0202 electrical engineering electronic engineering information engineering FOS: Electrical engineering electronic engineering information engineering Effective method General Materials Science Electrical Engineering and Systems Science - Signal Processing Interferometer Reliability (statistics) 0105 earth and related environmental sciences Signal processing General Engineering Wavelet transform 020206 networking & telecommunications Lightning Azimuth magnetic direction finder time of arrival lightning mapping Data mining Noise (video) lcsh:Electrical engineering. Electronics. Nuclear engineering computer lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 8, Pp 190064-190082 (2020) |
| Popis: | Despite the significant progress made in studying the lightning phenomenon, precise location and mapping of its occurrence remain a challenge. Lightning mapping can be determined by studying the electromagnetic radiation accompanying the lightning discharges. It can contribute substantially to efforts made to protect lives and valuable assets. There are three main methods used to locate lightning, which are Magnetic Direction Finder (MDF), Time of Arrival (TOA), and Interferometer (ITF). A thorough study of these methods provides researchers with a guide to better understand and progress in this field. This paper reviews existing approaches used to locate and map lightning within these three methods. We study the implemented techniques, analyze their merits and demerits, and sort them in a way that facilitates extracting opportunities for further improvements. We conclude that for better development in determining the location and map of lightning, improving the processing of lightning signals and filtering the associated noise with it is essential. This includes introducing new processing methods such as wavelet transformation instead of the traditional cross-correlation. The use of artificial intelligence may also contribute a lot, particularly deep learning, to determining the type of lightning, which enables better mapping for the lightning and its occurrence. We also could conclude that unlike MDF and TOA, which can locate the lightning strike points, ITF can produce lightning discharge propagation images that can unveil the mechanism of lightning discharges. Finally, this paper serves as a reference for researchers focusing on lightning mapping to give them insight into the field. 24 pages, 5 figures |
| Databáze: | OpenAIRE |
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