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<article article-type="research-article" dtd-version="1.3" 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" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">izvestswsu</journal-id><journal-title-group><journal-title xml:lang="ru">Известия Юго-Западного государственного университета</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of the Southwest State University</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2223-1560</issn><issn pub-type="epub">2686-6757</issn><publisher><publisher-name>ЮЗГУ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21869/2223-1560-2023-27-2-140-154</article-id><article-id custom-type="elpub" pub-id-type="custom">izvestswsu-1160</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Информатика, вычислительная техника и управление</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Computer science, computer engineering and IT managment</subject></subj-group></article-categories><title-group><article-title>Фильтрация сложных сигналов на основе двухуровневой нечетко-логической модели</article-title><trans-title-group xml:lang="en"><trans-title>Filtering of Complex Signals Based on a Two-Level Fuzzy-Logic Model</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Архипов</surname><given-names>А. Е.</given-names></name><name name-style="western" xml:lang="en"><surname>Arkhipov</surname><given-names>A. E.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Архипов Александр Евгеньевич, кандидат технических наук</p><p>ул. 50 лет Октября, д. 94, г. Курск 305040, Российская Федерация</p></bio><bio xml:lang="en"><p>Alexander E. Arkhipov, Cand. of Sci. (Engineering)</p><p>50 Let Oktyabrya str. 94, Kursk 305040, Russian Federation</p></bio><email xlink:type="simple">alex.76_09@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Юго-Западный государственный университет</institution></aff><aff xml:lang="en"><institution>Southwest State University</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>19</day><month>12</month><year>2023</year></pub-date><volume>27</volume><issue>2</issue><fpage>140</fpage><lpage>154</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Архипов А.Е., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Архипов А.Е.</copyright-holder><copyright-holder xml:lang="en">Arkhipov A.E.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://izvestswsu.elpub.ru/jour/article/view/1160">https://izvestswsu.elpub.ru/jour/article/view/1160</self-uri><abstract><sec><title>Цель исследования</title><p>Цель исследования. Разработка метода фильтрации и бинаризации сложных аналоговых радиосигналов, таких как сигнал автоматического зависимого наблюдения-вещания (АЗН-В), позволяющих повысить чувствительность приемника сигнала АЗН-В и увеличить количество корректно декодированных принятых сообщений.</p></sec><sec><title>Методы</title><p>Методы. Для решения поставленной задачи в работе были применены основы теории фильтрации сигналов и теории нечетких множеств. Предложенный метод основан на совмещении фильтрации сигнала с помощью известных фильтров и двухуровневой нечеткой модели. Первый и второй уровень нечеткой модели содержат три операции: автоматического формирования функций принадлежности, композиционного вывода и дефаззификации. Входные переменные обоих уровней задаются трапециевидными функциями принадлежности. На первом уровне они формируются автоматически в зависимости от характеристик сложного сигнала. Функция вывода на первом уровне задается одноэлементной функцией, а дефаззификация выполняется с использованием упрощенной модели центра тяжести.</p></sec><sec><title>Результаты</title><p>Результаты. Предложенный метод был реализован в разработанном устройстве на базе программируемой логической интегральной схемы (ПЛИС). Кроме фильтрации, разработанное устройство реализует все функции обработки сигнала, такие как: прием входных данных, декодирование, проверка корректности декодированных данных, хранение и передача сообщений АЗН-В для дальнейшей обработки. Отличительной особенностью устройства являются малые габариты и небольшое энергопотребление, что позволяет использовать его в малых космических аппаратах (МКА) и беспилотных летательных аппаратах.</p></sec><sec><title>Заключение</title><p>Заключение. Рассмотрен метод фильтрации сложных сигналов на основе нечетко-логической модели, который может применяться для фильтрации сложных сигналов, таких, как сообщения АЗН-В в модулях МКА. Предложенная реализация метода фильтрации позволяет повысить чувствительность приемника сигнала АЗН-В примерно на 20% и правильно декодировать принятый сигнал. Метод был реализован устройством на базе ПЛИС, что позволило уменьшить габариты и энергопотребление по сравнению с аналогами.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Purpose of research</title><p>Purpose of research. Development of a method and algorithm of complex analog radio signals filtering and binarization, such as the signal of Automatic dependent surveillance-broadcast (ADS-B), which allows to increase the sensitivity of the receiver of the AZN-B signal and increase the number of correctly detected received messages.</p></sec><sec><title>Methods</title><p>Methods. To solve this problem, the basics of the theory of signal filtering and the theory of fuzzy sets were applied in the work. The proposed method is based on combining signal filtering by known filters and a two-level fuzzy model. The first and second levels of the fuzzy model contain three operations: automatic formation of membership functions, compositional output and defuzzification. Input variables of both levels are given by trapezoidal membership functions. At the first level, they are formed automatically depending on the characteristics of the complex signal. The output function at the first level is given by a singleton function, and defuzzification is carried out using a simplified center of gravity model.</p></sec><sec><title>Results</title><p>Results. The proposed algorithm was implemented in the developed device based on a programmable logic integrated circuit (FPGA). In addition to filtering, the developed device implements all signal processing functions, such as: receiving input data, decoding, checking the correctness of decoded data, storing them, transmitting ADS-B messages for further processing. A distinctive feature of the device is its small size and low power consumption, which allows use it in small spacecraft and unmanned aerial vehicles.</p></sec><sec><title>Conclusion</title><p>Conclusion. A method of filtering complex signals based on a fuzzy logic model is considered, which can be used to filter complex signals, such as ADS-B messages in small spacecraft modules. The proposed implementation of the filtering method makes it possible to increase the sensitivity of the AZN-B signal receiver by 20% and correctly decode the received signal. The method was implemented by an FPGA-based device, which made it possible to reduce the size and power consumption compared to analogues.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>АЗН-В</kwd><kwd>нечеткая логика</kwd><kwd>фильтрация сложных сигналов</kwd><kwd>нечеткий фильтр</kwd></kwd-group><kwd-group xml:lang="en"><kwd>ADS-B</kwd><kwd>fuzzy logic</kwd><kwd>filtering complex signals</kwd><kwd>fuzzy filter</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Ghosh S.K., Ghosh A., Bhattacharyya S. Recognition of cancer mediating biomarkers using rough approximations enabled intuitionistic fuzzy soft sets based similarity measure // Applied Soft Computing, 2022. Vol. 124. P. 109052. https://doi.org/10.1016/ j.asoc.2022.109052.</mixed-citation><mixed-citation xml:lang="en">Ghosh S.K., Ghosh A., Bhattacharyya S. 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