Uncertainty Propagation Using Hybrid Methods

• Juan Félix San-Juan ^[1] ; Montserrat San-Martín ^[2] ; Iván Pérez ^[1] ; Rosario López ^[1] ; Edna Segura ^[1] ; Hans Carrillo ^[1]
  1. [1] Universidad de La Rioja

     Universidad de La Rioja

     Logroño, España

     
  2. [2] Universidad de Granada

     Universidad de Granada

     Granada, España

     
• Localización: 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020 / coord. por Álvaro Herrero Cosío, Carlos Cambra Baseca, Daniel Urda Muñoz, Javier Sedano Franco, Héctor Quintián Pardo, Emilio Santiago Corchado Rodríguez, 2021, ISBN 978-3-030-57802-2, págs. 709-717
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Small corrections in the argument of the latitude can be used to improve the accuracy of the SGP4 orbit propagator. These corrections have been obtained by applying the hybrid methodology for orbit propagation to SGP4, therefore yielding a hybrid version of this propagator. The forecasting part of the hybrid method is based on a state-space formulation of the exponential smoothing method. If the error terms that have to be considered during the model fitting process are taken as Gaussian noise, then the maximum-likelihood method can be applied so as to estimate the parameters of the exponential-smoothing model, as well as to compute the forecast together with its confidence interval. Finally, this hybrid SGP4 orbit propagator has been applied to data from Galileo-type orbits. This new propagator improves the accuracy of the classical SGP4, especially for short forecasting horizons.