pimiПриборы и методы измеренийDevices and Methods of Measurements2220-95062414-0473BNTU10.21122/2220-9506-2021-12-4-272-279pimi-731Research ArticleСредства измеренийMeasuring instrumentsАвтономное потоковое детектирование космических объектов на базе удалённой оптической системыAutonomous Streaming Space Objects Detection Based on a Remote Optical SystemБарановаВ. С.BaranovaV. S.

Адрес для переписки: Баранова В.С. – Белорусский государственный университет, пр–т Независимости, 4, г. Минск 220030 e-mail: rct.baranovaVS@bsu.by

Address for correspondence: Baranova V.S. – Belarusian State University, Nezavisimosti Ave., 4, Minsk 220030, Belarus e-mail: rct.baranovaVS@bsu.by

rct.baranovaVS@bsu.byСаечниковВ. А.SaetchnikovV. A.

пр-т Независимости, 4, г. Минск 220030

Nezavisimosti Ave., 4, Minsk 220030

СпиридоновА. А.SpiridonovA. A.

пр-т Независимости, 4, г. Минск 220030

Nezavisimosti Ave., 4, Minsk 220030

Белорусский государственный университетБеларусьBelarusian State UniversityBelarus202122122021124272279Copyright © Баранова В.С., Саечников В.А., Спиридонов А.А., 20212021Баранова В.С., Саечников В.А., Спиридонов А.А.Baranova V.S., Saetchnikov V.A., Spiridonov A.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://pimi.bntu.by/jour/article/view/731

Привычные методы обработки стационарных изображений обеспечивают устойчивую результативность как в области астрометрии объектов глубокого космоса, так и в прикладных задачах определения параметров орбит искусственных спутников. Но быстродействие вычислительной архитектуры и функции малых оптических систем стремительно развиваются, что способствует возможности использования динамического видеопотока в приложении детектирования и инициализации космических объектов. Цель данной работы – автоматизировать процесс обнаружения и обработки данных оптических измерений космических объектов при мониторинге околоземного пространства и численных методах определения орбит.

В работе предлагается реализация малобюджетной автономной оптической системы детектирования космических объектов с элементами удалённого управления. Аппаратное и программное исполнение реализовано и протестировано в формате встраиваемой программной системы на базе Linux-ядра одноплатного компьютера Raspberry Pi и модульной камеры. В лабораторных условиях проведено макетное моделирование траектории движения спутника для предварительной оценки эффективности работы скомпилированных алгоритмических модулей библиотеки компьютерного зрения OpenCV.

На основании результатов моделирования выполнено экспериментальное динамическое обнаружение международной космической станции в режиме реального времени из точки наблюдения с координатами 25°41′49″ в.д. 53°52′36″ с.ш. в промежутке 00:54:00–00:54:30 17.07.2021 (UTC + 03:00). Продемонстрирован результат обработки видеосъёмки пролёта в виде массива координат центроида международной космической станции в плоскости изображения с временными метками периодичностью 0,2 с.

Такой подход обеспечивает автономное извлечение предварительных данных с последующей их конвертацией в угловые координаты космического объекта для численных методов начального определения его орбиты.

Traditional image processing techniques provide sustainable efficiency in the astrometry of deep space objects and in applied problems of determining the parameters of artificial satellite orbits. But the speed of the computing architecture and the functions of small optical systems are rapidly developing thus contribute to the use of a dynamic video stream for detecting and initializing space objects. The purpose of this paper is to automate the processing of optical measurement data during detecting space objects and numerical methods for the initial orbit determination.

This article provided the implementation of a low-cost autonomous optical system for detecting of space objects with remote control elements. The basic algorithm model had developed and tested within the framework of remote control of a simplified optical system based on a Raspberry Pi 4 single-board computer with a modular camera. Under laboratory conditions, the satellite trajectory had simulated for an initial assessment of the compiled algorithmic modules of the computer vision library OpenCV.

Based on the simulation results, dynamic detection of the International Space Station in real-time from the observation site with coordinates longitude 25o41′49″ East, latitude 53o52′36″ North in the interval 00:54:00–00:54:30 17.07.2021 (UTC + 03:00) had performed. The video processing result of the pass had demonstrated in the form of centroid coordinates of the International Space Station in the image plane with a timestamps interval of which is 0.2 s.

This approach provides an autonomous raw data extraction of a space object for numerical methods for the initial determination of its orbit.

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The authors declare that there are no conflicts of interest present.