Universiti Teknologi Malaysia Institutional Repository

An adaptation of deep learning technique in orbit propagation model using long short-term memory

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.


Official URL: http://dx.doi.org/10.1109/ICECCE52056.2021.9514264


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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:deep learning, long short-term memory, orbit propagation
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:96026
Deposited By: Narimah Nawil
Deposited On:01 Jul 2022 16:45
Last Modified:01 Jul 2022 16:45

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