Cosmic ResearchCosmic ResearchКосмические исследования0023-42063034-5502The Russian Academy of Sciences69671510.31857/S0023420625050019ArticlesСтатьиResearch ArticleBayesian meteor reconstruction using the PAIP-V dataБайесовская реконструкция метеоров по данным многоканального детектора PAIP-VSharakinS. A.ШаракинС. А.saraev.re17@physics.msu.ruSaraevR. E.СараевР. Е.saraev.re17@physics.msu.ruSkobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State UniversityНаучно-исследовательский институт ядерной физики имени Д.В. Скобельцына МГУ имени М.В. ЛомоносоваLomonosov Moscow State University, Faculty of PhysicsМГУ имени М.В. Ломоносова, Физический факультет15092025635VOL 63, NO5 (2025)ТОМ 63, №5 (2025)45347021112025Copyright ©; 2025, Russian Academy of SciencesCopyright ©; 2025, Российская академия наук2025Russian Academy of SciencesРоссийская академия наукhttps://journals.eco-vector.com/0023-4206/article/view/696715

The paper considers the reconstruction problem of events registered by orbital and ground-based detectors with low angular but high temporal resolution. It is shown that in such a situation it is still possible to obtain highly accurate spatiotemporal reconstruction if one combines information on both the geometry and kinematics of the motion and its dynamics (luminescence curve) within a single algorithm. This is especially important in the presence of multiple structural gaps between photodetector channels when only a portion of the event is recorded. In this paper, a Bayesian method implemented by means of the PyMC library is proposed for the reconstruction of track events (tracks of meteors, satellites, etc.): the parametric model takes into account both the features of the event itself and the process of its registration, and the posterior distribution of the parameters is constructed using MCMC sampling. The method is tested on the example of a small sample of meteors of the Geminid-2022 meteor shower recorded by the PAIP-V ground-based detector installed in the Murmansk region.

В работе рассматривается проблема реконструкции событий, регистрируемых орбитальными и наземными детекторами с низким угловым, но высоким временным разрешением. Показано, что в такой ситуации все еще можно получить высокоточную пространственно-временную реконструкцию, если в рамках единого алгоритма объединить информацию как о геометрии и кинематике движения, так и его динамике (кривой свечения). Это особенно важно при наличии многочисленных конструктивных зазоров между каналами фотоприемника, когда регистрируется лишь часть события. В настоящей работе для реконструкции трековых событий (треков метеоров, спутников и т.п.) предложен байесовский метод, реализованный средствами библиотеки PyMC: параметрическая модель учитывает как особенности самого явления, так и процесса его регистрации, а апостериорное распределение на параметры строится при помощи MCMC-сэмплирования. Апробация метода осуществлена на примере небольшой выборки метеоров потока Геминиды-2022, зарегистрированных наземным детектором PAIP-V, установленным в Мурманской области.

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