An adaptation of deep learning technique in orbit propagation model using long short-term memory
The orbit propagation model is used to predict the position and velocity of the satellites. It is crucial to obtain accurate predictions to ensure that satellite operation planning is in place and detects any possible disasters. However, the model's accuracy decreases as the propagation span in...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/96026/1/NorasnilawatiSalleh2021_AnAdaptationofDeepLearning.pdf |
| _version_ | 1796866139759837184 |
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| author | Salleh, N. Mohd. Azmi, N. F. Yuhaniz, S. S. |
| author_facet | Salleh, N. Mohd. Azmi, N. F. Yuhaniz, S. S. |
| author_sort | Salleh, N. |
| collection | ePrints |
| description | The orbit propagation model is used to predict the position and velocity of the satellites. It is crucial to obtain accurate predictions to ensure that satellite operation planning is in place and detects any possible disasters. However, the model's accuracy decreases as the propagation span increases if the input data are not updated. Therefore, to minimize these errors while still maintaining the model accuracy, a study is conducted. The Simplified General Perturbations-4 (SGP4) model and two-line elements (TLE) data are selected to perform this study. The problem is analyzed, and the deep learning technique is the proposed method to solve the issue. Next, the enhanced model is validated. The study aims to produce a reliable orbit propagation model and assist the satellite's operational planning. Also, the improved model can provide vital information for space-based organizations and anyone who may be affected. |
| first_indexed | 2024-03-05T21:07:42Z |
| format | Conference or Workshop Item |
| id | utm.eprints-96026 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T21:07:42Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | utm.eprints-960262022-07-01T08:45:52Z http://eprints.utm.my/96026/ An adaptation of deep learning technique in orbit propagation model using long short-term memory Salleh, N. Mohd. Azmi, N. F. Yuhaniz, S. S. T Technology (General) The orbit propagation model is used to predict the position and velocity of the satellites. It is crucial to obtain accurate predictions to ensure that satellite operation planning is in place and detects any possible disasters. However, the model's accuracy decreases as the propagation span increases if the input data are not updated. Therefore, to minimize these errors while still maintaining the model accuracy, a study is conducted. The Simplified General Perturbations-4 (SGP4) model and two-line elements (TLE) data are selected to perform this study. The problem is analyzed, and the deep learning technique is the proposed method to solve the issue. Next, the enhanced model is validated. The study aims to produce a reliable orbit propagation model and assist the satellite's operational planning. Also, the improved model can provide vital information for space-based organizations and anyone who may be affected. 2021 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/96026/1/NorasnilawatiSalleh2021_AnAdaptationofDeepLearning.pdf Salleh, N. and Mohd. Azmi, N. F. and Yuhaniz, S. S. (2021) An adaptation of deep learning technique in orbit propagation model using long short-term memory. In: 3rd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2021, 12 June 2021 - 13 June 2021, Kuala Lumpur, Malaysia. http://dx.doi.org/10.1109/ICECCE52056.2021.9514264 |
| spellingShingle | T Technology (General) Salleh, N. Mohd. Azmi, N. F. Yuhaniz, S. S. An adaptation of deep learning technique in orbit propagation model using long short-term memory |
| title | An adaptation of deep learning technique in orbit propagation model using long short-term memory |
| title_full | An adaptation of deep learning technique in orbit propagation model using long short-term memory |
| title_fullStr | An adaptation of deep learning technique in orbit propagation model using long short-term memory |
| title_full_unstemmed | An adaptation of deep learning technique in orbit propagation model using long short-term memory |
| title_short | An adaptation of deep learning technique in orbit propagation model using long short-term memory |
| title_sort | adaptation of deep learning technique in orbit propagation model using long short term memory |
| topic | T Technology (General) |
| url | http://eprints.utm.my/96026/1/NorasnilawatiSalleh2021_AnAdaptationofDeepLearning.pdf |
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