RoBo6: Standardized MMT Light Curve Dataset for Rocket Body Classification
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913592128831488 |
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| author | Kyselica, Daniel Šuppa, Marek Šilha, Jiří Ďurikovič, Roman |
| author_facet | Kyselica, Daniel Šuppa, Marek Šilha, Jiří Ďurikovič, Roman |
| contents | Space debris presents a critical challenge for the sustainability of future space missions, emphasizing the need for robust and standardized identification methods. However, a comprehensive benchmark for rocket body classification remains absent. This paper addresses this gap by introducing the RoBo6 dataset for rocket body classification based on light curves. The dataset, derived from the Mini Mega Tortora database, includes light curves for six rocket body classes: CZ-3B, Atlas 5 Centaur, Falcon 9, H-2A, Ariane 5, and Delta 4. With 5,676 training and 1,404 test samples, it addresses data inconsistencies using resampling, normalization, and filtering techniques. Several machine learning models were evaluated, including CNN and transformer-based approaches, with Astroconformer reporting the best performance. The dataset establishes a common benchmark for future comparisons and advancements in rocket body classification tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_00544 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | RoBo6: Standardized MMT Light Curve Dataset for Rocket Body Classification Kyselica, Daniel Šuppa, Marek Šilha, Jiří Ďurikovič, Roman Computer Vision and Pattern Recognition Instrumentation and Methods for Astrophysics Machine Learning Image and Video Processing Space debris presents a critical challenge for the sustainability of future space missions, emphasizing the need for robust and standardized identification methods. However, a comprehensive benchmark for rocket body classification remains absent. This paper addresses this gap by introducing the RoBo6 dataset for rocket body classification based on light curves. The dataset, derived from the Mini Mega Tortora database, includes light curves for six rocket body classes: CZ-3B, Atlas 5 Centaur, Falcon 9, H-2A, Ariane 5, and Delta 4. With 5,676 training and 1,404 test samples, it addresses data inconsistencies using resampling, normalization, and filtering techniques. Several machine learning models were evaluated, including CNN and transformer-based approaches, with Astroconformer reporting the best performance. The dataset establishes a common benchmark for future comparisons and advancements in rocket body classification tasks. |
| title | RoBo6: Standardized MMT Light Curve Dataset for Rocket Body Classification |
| topic | Computer Vision and Pattern Recognition Instrumentation and Methods for Astrophysics Machine Learning Image and Video Processing |
| url | https://arxiv.org/abs/2412.00544 |