Efficient Multi-Threaded Data Starting Point Matching Method for Space Target Cataloging
Currently, multi-target survey telescope arrays play an important role in the build-up and maintenance of space object catalog databases, collecting massive observational data without attributing information. However, the matching process of massive observational data poses significant challenges to...
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MDPI AG
2025-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/8/2367 |
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| author | Jiannan Sun Zhe Kang Zhenwei Li Cunbo Fan |
| author_facet | Jiannan Sun Zhe Kang Zhenwei Li Cunbo Fan |
| author_sort | Jiannan Sun |
| collection | DOAJ |
| description | Currently, multi-target survey telescope arrays play an important role in the build-up and maintenance of space object catalog databases, collecting massive observational data without attributing information. However, the matching process of massive observational data poses significant challenges to traditional prediction methods. To address the issues of low matching success rates and prolonged computation times in traditional methods, this paper proposes a multi-threaded data starting point matching method. First, orbital elements from the Space Surveillance and Tracking (SST) database are extracted for two days before and after the observation moment. A set of orbital elements closest to the observation epoch is filtered to form the primary candidate catalog containing the maximum number of objects. A matching error threshold is set. Second, multi-threaded traversal of the primary candidate catalog is performed to calculate observation residuals with the data starting point using an orbit prediction procedure. Orbital elements meeting the triple matching error threshold are selected to form the secondary candidate catalog, which is used in the entire data arc segment-matching calculation. Finally, the root mean square error (RMSE) of observation residuals for the entire data arc segment is computed point by point. The orbital elements satisfying the matching threshold are identified as matching results based on the principle of optimality. Experimental results demonstrate that with a matching error threshold of 1°, the proposed method achieves an average matching success rate of 97.62% for data arc segments with nearly 10,000 passes per day over 8 consecutive days. In the SST database containing an average of 25,720 targets, this method processes an average of 2164 data arc segments per minute, improving matching efficiency by 115 times compared to traditional prediction methods. |
| format | Article |
| id | doaj-art-03e51ac10f8f494aaf781267ef3d201a |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-03e51ac10f8f494aaf781267ef3d201a2025-08-20T02:18:15ZengMDPI AGSensors1424-82202025-04-01258236710.3390/s25082367Efficient Multi-Threaded Data Starting Point Matching Method for Space Target CatalogingJiannan Sun0Zhe Kang1Zhenwei Li2Cunbo Fan3Changchun Observatory, National Astronomical Observatories, Chinese Academy of Sciences, Changchun 130117, ChinaChangchun Observatory, National Astronomical Observatories, Chinese Academy of Sciences, Changchun 130117, ChinaChangchun Observatory, National Astronomical Observatories, Chinese Academy of Sciences, Changchun 130117, ChinaChangchun Branch, Chinese Academy of Sciences, Changchun 130022, ChinaCurrently, multi-target survey telescope arrays play an important role in the build-up and maintenance of space object catalog databases, collecting massive observational data without attributing information. However, the matching process of massive observational data poses significant challenges to traditional prediction methods. To address the issues of low matching success rates and prolonged computation times in traditional methods, this paper proposes a multi-threaded data starting point matching method. First, orbital elements from the Space Surveillance and Tracking (SST) database are extracted for two days before and after the observation moment. A set of orbital elements closest to the observation epoch is filtered to form the primary candidate catalog containing the maximum number of objects. A matching error threshold is set. Second, multi-threaded traversal of the primary candidate catalog is performed to calculate observation residuals with the data starting point using an orbit prediction procedure. Orbital elements meeting the triple matching error threshold are selected to form the secondary candidate catalog, which is used in the entire data arc segment-matching calculation. Finally, the root mean square error (RMSE) of observation residuals for the entire data arc segment is computed point by point. The orbital elements satisfying the matching threshold are identified as matching results based on the principle of optimality. Experimental results demonstrate that with a matching error threshold of 1°, the proposed method achieves an average matching success rate of 97.62% for data arc segments with nearly 10,000 passes per day over 8 consecutive days. In the SST database containing an average of 25,720 targets, this method processes an average of 2164 data arc segments per minute, improving matching efficiency by 115 times compared to traditional prediction methods.https://www.mdpi.com/1424-8220/25/8/2367optical data processingorbit predictiondata matchingmulti-threaded technologyspace targets |
| spellingShingle | Jiannan Sun Zhe Kang Zhenwei Li Cunbo Fan Efficient Multi-Threaded Data Starting Point Matching Method for Space Target Cataloging Sensors optical data processing orbit prediction data matching multi-threaded technology space targets |
| title | Efficient Multi-Threaded Data Starting Point Matching Method for Space Target Cataloging |
| title_full | Efficient Multi-Threaded Data Starting Point Matching Method for Space Target Cataloging |
| title_fullStr | Efficient Multi-Threaded Data Starting Point Matching Method for Space Target Cataloging |
| title_full_unstemmed | Efficient Multi-Threaded Data Starting Point Matching Method for Space Target Cataloging |
| title_short | Efficient Multi-Threaded Data Starting Point Matching Method for Space Target Cataloging |
| title_sort | efficient multi threaded data starting point matching method for space target cataloging |
| topic | optical data processing orbit prediction data matching multi-threaded technology space targets |
| url | https://www.mdpi.com/1424-8220/25/8/2367 |
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