Current results on recognition of whistlers and atmospherics, as well as data from lightning localization systems, are the initial data for the proposed algorithm for determining the coordinates of the radiating lightning by separate groups of registered whistlers. When we register in the receiving point a whistler sequence, a search is performed in lightning localization systems of such a limited region in which a close time sequence of registration of lightning was detected in a given time window. The search time window can be refined by detecting at the whistler receiving point the previous close time sequence of registered atmospherics with similar difference-time deviations.
During analyzing of geophysical data, the problem of highlighting a form of geophysical signals often appears. In this work, it is proposed to use deep learning, which is currently one of the top priorities in the field of artificial intelligence and machine learning. The samples of geophysical signals, as well as the generated samples of signals by their mathematical models and typical examples of forms, act as a training dataset for deep neural network. End-to-end demonstration examples of the highlighting of reflection traces from different layers of the ionosphere in the ionograms, as well as the highlighting of whistler forms in the VLF spectrograms are presented.
The authors discuss problems of constructing a multi-site system for lightning activity monitoring aimed at analyzing the structure of tropical cyclones using a network of receivers of VLF radio signals. We propose a functional scheme for the construction of a monitoring system, which includes a functional block to synthesize the system structure, using the existing authorial multi-agent bio-inspired algorithm for synthesizing the sensor network structure.
In the region of the Northern group of volcanoes in Kamchatka peninsula, a distributed network is being planned to monitor the VLF range electromagnetic radiation and to locate the lightning strokes. It will allow the researchers to register weaker electromagnetic pulses from lightning strokes in comparison to the World Wide Lightning Location Network. The hardware-software complex of the network under construction is presented. The capabilities of the available and the developing hardware and software to investigate natural phenomena associated with lightning activity are described.
Topical problems of monitoring and analysis of lightning activity are considered. The paper also presents monthly distributions of lightning discharges over the globe. The instrumentation applied in VLF signal registration is described. An algorithm of search for possible areas of lightning activity affecting whistler occurrence in a defined region is suggested. The algorithm compares each detected whistler with the data of the World Wide Lightning Location Network. It also may be used to analyze different time intervals of the world lightning activity from the moment of whistler formation.
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