The use of a neural network in solving problems of recognition and classification of spacecraft by their optical images
In recent years, the number of space objects located in near-Earth outer space, especially in the near operational zone, has increased significantly due to the build-up of space groupings, including dual-use (for example, Starlink) and the remnants of their vital activity (space debris). This factor...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | Russian |
| Published: |
Association «Technology Platform «National Information Satellite System»
2023-03-01
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| Series: | Космические аппараты и технологии |
| Subjects: | |
| Online Access: | http://journal-niss.ru/en/archive_view.php?num=299 |
| _version_ | 1797847923414794240 |
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| author | K. I. Kushchenko Yu. V. Zheleznyakov A. V. Voloshchuk A. A. Filonov A. A. Tolmachev |
| author_facet | K. I. Kushchenko Yu. V. Zheleznyakov A. V. Voloshchuk A. A. Filonov A. A. Tolmachev |
| author_sort | K. I. Kushchenko |
| collection | DOAJ |
| description | In recent years, the number of space objects located in near-Earth outer space, especially in the near operational zone, has increased significantly due to the build-up of space groupings, including dual-use (for example, Starlink) and the remnants of their vital activity (space debris). This factor increases the importance of the task of recognizing and classifying space objects by type in the shortest possible time and entering them into the main catalog of space objects. The developed methodology allows automated analysis of optical images of space objects using software to solve the problem of their recognition and classification by type using a convolutional neural network. The purpose of the study is to increase the efficiency of processing and analysis of optical images of spacecraft. The experimental results of the study confirm the achievement of the research goal. The developed methodology contributes to the development of software and hardware for image processing and can be used in calculations and data preparation for information support of interested officials. For the first time, a training set for a convolutional neural network has been prepared using real optical images of spacecraft obtained in the visible range. |
| first_indexed | 2024-04-09T18:19:06Z |
| format | Article |
| id | doaj.art-aa33b663e99b4bc68e39d2c6192aaa23 |
| institution | Directory Open Access Journal |
| issn | 2618-7957 |
| language | Russian |
| last_indexed | 2024-04-09T18:19:06Z |
| publishDate | 2023-03-01 |
| publisher | Association «Technology Platform «National Information Satellite System» |
| record_format | Article |
| series | Космические аппараты и технологии |
| spelling | doaj.art-aa33b663e99b4bc68e39d2c6192aaa232023-04-12T11:27:36ZrusAssociation «Technology Platform «National Information Satellite System»Космические аппараты и технологии2618-79572023-03-0171515910.26732/j.st.2023.1.06The use of a neural network in solving problems of recognition and classification of spacecraft by their optical imagesK. I. Kushchenko0Yu. V. Zheleznyakov1A. V. Voloshchuk2A. A. Filonov3A. A. Tolmachev4Military unit 03863Mozhaisky Military Space AcademyMozhaisky Military Space AcademyMilitary Aerospace Defense AcademyMilitary Aerospace Defense AcademyIn recent years, the number of space objects located in near-Earth outer space, especially in the near operational zone, has increased significantly due to the build-up of space groupings, including dual-use (for example, Starlink) and the remnants of their vital activity (space debris). This factor increases the importance of the task of recognizing and classifying space objects by type in the shortest possible time and entering them into the main catalog of space objects. The developed methodology allows automated analysis of optical images of space objects using software to solve the problem of their recognition and classification by type using a convolutional neural network. The purpose of the study is to increase the efficiency of processing and analysis of optical images of spacecraft. The experimental results of the study confirm the achievement of the research goal. The developed methodology contributes to the development of software and hardware for image processing and can be used in calculations and data preparation for information support of interested officials. For the first time, a training set for a convolutional neural network has been prepared using real optical images of spacecraft obtained in the visible range.http://journal-niss.ru/en/archive_view.php?num=299neural networkspacecraftoptical imagesclassification |
| spellingShingle | K. I. Kushchenko Yu. V. Zheleznyakov A. V. Voloshchuk A. A. Filonov A. A. Tolmachev The use of a neural network in solving problems of recognition and classification of spacecraft by their optical images Космические аппараты и технологии neural network spacecraft optical images classification |
| title | The use of a neural network in solving problems of recognition and classification of spacecraft by their optical images |
| title_full | The use of a neural network in solving problems of recognition and classification of spacecraft by their optical images |
| title_fullStr | The use of a neural network in solving problems of recognition and classification of spacecraft by their optical images |
| title_full_unstemmed | The use of a neural network in solving problems of recognition and classification of spacecraft by their optical images |
| title_short | The use of a neural network in solving problems of recognition and classification of spacecraft by their optical images |
| title_sort | use of a neural network in solving problems of recognition and classification of spacecraft by their optical images |
| topic | neural network spacecraft optical images classification |
| url | http://journal-niss.ru/en/archive_view.php?num=299 |
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