Neural Networks for Searching for Meteoral Signals in the Data of the Orbital Telescope “UV Atmosphere”
- 作者: Zotov M.1, Sokolinskii D.2, Arifullin A.2
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隶属关系:
- Skobeltsyn Institute of Nuclear Physics, Moscow State University
- Moscow State University
- 期: 卷 100, 编号 6 (2023)
- 页面: 557-566
- 栏目: Articles
- URL: https://journals.rcsi.science/0004-6299/article/view/139095
- DOI: https://doi.org/10.31857/S0004629923060105
- EDN: https://elibrary.ru/VBIJUW
- ID: 139095
如何引用文章
详细
Since 2019, the Russian–Italian experiment “UV Atmosphere” (Mini-EUSO) has been operational on the International Space Station. The primary instrument of this experiment is a wide-angle telescope positioned toward nadir. Its main objective is to generate an ultraviolet map of the Earth’s nocturnal atmosphere radiation. This map serves as a crucial element in the preparation of a large-scale experiment involving the study of extremely high-energy cosmic rays using an orbiting telescope. Similar to the preceding TUS experiment, the “UV Atmosphere” instrument detects signals from various atmospheric processes in the ultraviolet range, including the luminosity of meteors. In this paper, we describe two simple neural networks that effectively extract meteor signals from the overall data stream. The proposed approach can also be applied to identify track-like signals of various origins in the data obtained from fluorescent and Cherenkov telescopes.
作者简介
M. Zotov
Skobeltsyn Institute of Nuclear Physics, Moscow State University
Email: zotov@eas.sinp.msu.ru
Moscow, Russia
D. Sokolinskii
Moscow State University
Email: zotov@eas.sinp.msu.ru
Moscow, Russia
A. Arifullin
Moscow State University
编辑信件的主要联系方式.
Email: zotov@eas.sinp.msu.ru
Moscow, Russia
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