Hybrid orbit propagator based on neural networks. Multivariate time series forecasting approach
- Hans Carrillo 1
- Edna Segura 1
- Rosario López 1
- Iván Pérez 1
- Juan Félix San-Juan 1
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1
Universidad de La Rioja
info
- Hugo Sanjurjo González (ed. lit.)
- Iker Pastor López (ed. lit.)
- Pablo García Bringas (ed. lit.)
- Héctor Quintián (ed. lit.)
- Emilio Corchado (ed. lit.)
Editorial: Springer
ISSN: 2194-5357
ISBN: 978-3-030-87868-9
Año de publicación: 2022
Volumen: 1401
Páginas: 695-705
Congreso: 16th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO (16º. 2021. Bilbao)
Tipo: Aportación congreso
Resumen
The orbital trajectory of artificial satellites around the Earthrequires frequent corrections in response to different perturbation forces.The necessary maneuvers can be designed in simulated space environ-ments by propagating Two Line Elements with orbit propagators such asSGP4, which provides the orbital position information at a given epoch.In this work, a hybrid orbit propagator based on a neural network modelis developed. Compared with previous models, the proposed neural net-work shows generalization capabilities for different space objects, whichimplies a potential benefit for the accuracy of any classical orbit propa-gator.