Neural Network Based Approach to Recognition of Meteor Tracks in the Mini-EUSO Telescope Data

Mini-EUSO is a wide-angle fluorescence telescope that registers ultraviolet (UV) radiation in the nocturnal atmosphere of Earth from the International Space Station. Meteors are among multiple phenomena that manifest themselves not only in the visible range but also in the UV. We present two simple...

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Published inAlgorithms Vol. 16; no. 9; p. 448
Main Authors Zotov, Mikhail, Anzhiganov, Dmitry, Kryazhenkov, Aleksandr, Barghini, Dario, Battisti, Matteo, Belov, Alexander, Bertaina, Mario, Bianciotto, Marta, Bisconti, Francesca, Blaksley, Carl, Blin, Sylvie, Cambiè, Giorgio, Capel, Francesca, Casolino, Marco, Ebisuzaki, Toshikazu, Eser, Johannes, Fenu, Francesco, Franceschi, Massimo, Golzio, Alessio, Gorodetzky, Philippe, Kajino, Fumiyoshi, Kasuga, Hiroshi, Klimov, Pavel, Manfrin, Massimiliano, Marcelli, Laura, Miyamoto, Hiroko, Murashov, Alexey, Napolitano, Tommaso, Ohmori, Hiroshi, Olinto, Angela, Parizot, Etienne, Picozza, Piergiorgio, Piotrowski, Lech, Plebaniak, Zbigniew, Prévôt, Guillaume, Reali, Enzo, Ricci, Marco, Romoli, Giulia, Sakaki, Naoto, Shinozaki, Kenji, De La Taille, Christophe, Takizawa, Yoshiyuki, Vrábel, Michal, Wiencke, Lawrence
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2023
Subjects
Artificial neural networks
atmosphere
Collaboration
Cosmic rays
Evaluation
Experiments
Fluorescence
fluorescence telescope
International Space Station
Machine learning
meteor
Meteors
Meteors & meteorites
neural network
Neural networks
orbital experiment
pattern recognition
Radiation
Recognition
Space stations
Telescope
Telescopes
Ultraviolet radiation
UV illumination
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Summary:Mini-EUSO is a wide-angle fluorescence telescope that registers ultraviolet (UV) radiation in the nocturnal atmosphere of Earth from the International Space Station. Meteors are among multiple phenomena that manifest themselves not only in the visible range but also in the UV. We present two simple artificial neural networks that allow for recognizing meteor signals in the Mini-EUSO data with high accuracy in terms of a binary classification problem. We expect that similar architectures can be effectively used for signal recognition in other fluorescence telescopes, regardless of the nature of the signal. Due to their simplicity, the networks can be implemented in onboard electronics of future orbital or balloon experiments.
ISSN:1999-4893
1999-4893
DOI:10.3390/a16090448