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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="other" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Sensory Systems</journal-id><journal-title-group><journal-title xml:lang="en">Sensory Systems</journal-title><trans-title-group xml:lang="ru"><trans-title>Сенсорные системы</trans-title></trans-title-group></journal-title-group><issn publication-format="print">0235-0092</issn><issn publication-format="electronic">3034-5936</issn><publisher><publisher-name xml:lang="en">The Russian Academy of Sciences</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">675821</article-id><article-id pub-id-type="doi">10.31857/S0235009223010092</article-id><article-id pub-id-type="edn">AULKIC</article-id><article-categories><subj-group subj-group-type="toc-heading"><subject>ТЕХНИЧЕСКОЕ ЗРЕНИЕ</subject></subj-group><subj-group subj-group-type="article-type"><subject></subject></subj-group></article-categories><title-group><article-title xml:lang="en">Automatic evaluation of the internal parameters of the onboard camera of a spacecraft from video data of dockings with the iss</article-title><trans-title-group xml:lang="ru"><trans-title>Автоматическая оценка фокусного расстояния бортовой камеры космического аппарата по видеоданным стыковки с МКС</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Zinov</surname><given-names>V. A.</given-names></name><name xml:lang="ru"><surname>Зинов</surname><given-names>В. А.</given-names></name></name-alternatives><email>konovalenko@iitp.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Konovalenko</surname><given-names>I. A.</given-names></name><name xml:lang="ru"><surname>Коноваленко</surname><given-names>И. А.</given-names></name></name-alternatives><email>konovalenko@iitp.ru</email><xref ref-type="aff" rid="aff3"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Institute for Information Transmission Problem RAS</institution></aff><aff><institution xml:lang="ru">Институт проблем передачи информации им. А.А. Харкевича РАН</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Moscow Institute of Physics and Technology (National Research University)</institution></aff><aff><institution xml:lang="ru">Московский физико-технический институт</institution></aff></aff-alternatives><aff-alternatives id="aff3"><aff><institution xml:lang="en">Moscow Institute of Physics and Technology (National Research University)</institution></aff><aff><institution xml:lang="ru">Институт проблем передачи информации им. А.А. Харкевича РАН</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2023-01-01" publication-format="electronic"><day>01</day><month>01</month><year>2023</year></pub-date><volume>37</volume><issue>1</issue><fpage>78</fpage><lpage>88</lpage><history><date date-type="received" iso-8601-date="2025-02-28"><day>28</day><month>02</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2023, Russian Academy of Sciences</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2023, Российская академия наук</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="en">Russian Academy of Sciences</copyright-holder><copyright-holder xml:lang="ru">Российская академия наук</copyright-holder></permissions><self-uri xlink:href="https://journals.eco-vector.com/0235-0092/article/view/675821">https://journals.eco-vector.com/0235-0092/article/view/675821</self-uri><abstract xml:lang="en"><p id="idm45181324853968">The KURS radio engineering system for measuring motion parameters during rendezvous and docking has some disadvantages: the accuracy of measurement with multiple reflections of the wave can drop, the technical equipment is available on both docking vehicles (active and passive parts), it is expensive both in terms of energy resources and in terms of cost. An analysis of existing visual systems has shown that such systems successfully solve the problems of visual odometry on UAVs, robots, and similar devices. However, to use such systems, it is necessary to know the internal parameters of the camera (calibration). Classical calibration using a checkerboard pattern is difficult to perform in outer space. In connection with all of the above, this paper proposes methods for estimating the focal length of the camera, based on the analysis of the available video sequence with the footage of the process of rendezvous of spacecraft. The proposed approaches are based on the maximum likelihood method (MLE) and maximum a posteriori estimation (MAP) of the functional depending on the Euler angles and focal length. The results of these methods are compared, showing the advantages of MAP over MLE and the possibility of their practical application.</p></abstract><trans-abstract xml:lang="ru"><p id="idm45181324852192">Радиотехническая система измерения параметров движения при сближении и стыковке “Курс” имеет некоторые недостатки: точность измерения при многократных переотражениях волны может падать; техническая аппаратура имеется на обоих стыкующихся аппаратах (активная и пассивная части), что является дорогостоящим; система затратна по энергетическим ресурсам. Анализ существующих зрительных систем показывает, что такие системы успешно решают задачи визуальной одометрии на БПЛА, роботах и подобных устройствах. Однако для применения таких систем необходимо знать внутренние параметры камеры (калибровка). Классическая калибровка с использованием шаблона типа “шахматная доска” трудновыполнима в космическом пространстве. В данной работе предлагаются методы оценки фокусного расстояния камеры, основанные на анализе имеющейся видеопоследовательности с отснятым процессом сближения космических аппаратов. Предложенные подходы основаны на методе максимального правдоподобия (MLE) и оценке апостериорного максимума (MAP) функционала, зависящего от углов Эйлера и фокусного расстояния. Сравнение результатов применения этих методов показывает достоинства MAP перед MLE и возможность их практического применения.</p></trans-abstract><kwd-group xml:lang="en"><kwd>focal length</kwd><kwd>camera estimation</kwd><kwd>spacecraft docking</kwd><kwd>automatic docking</kwd><kwd>maximum likelihood estimation</kwd><kwd>maximum a posteriori probability</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>фокусное расстояние</kwd><kwd>калибровка камеры</kwd><kwd>стыковка космических аппаратов</kwd><kwd>автоматическая стыковка</kwd><kwd>метод максимального правдоподобия</kwd><kwd>метод апостериорного максимума</kwd></kwd-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><citation-alternatives><mixed-citation xml:lang="en">Bakhshiev A.V., Korban P.A., Kirpan N.A. 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