Abstract
The high precision prediction of atomic clocks on board is a key technology for the long-term autonomous operation of a navigation satellite system. Some researches show that the performance of traditional prediction models of atomic clocks can not meet the requirements of practical applications. In order to improve the atomic clock error prediction accuracy, we propose a model based on functional network in this paper. According to the data characteristics of atomic clocks, the clock error series is firstly fit by polynomial and then the residuals is modeled by functional network. Finally, by using the data of GPS satellites, five independent prediction tests have been done to verify the model. The simulation results show that, compared with the traditional models, the proposed model can fit and predict clock error more effectively.
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Xu, B., Wang, Y. & Yang, X. Navigation Satellite Clock Error Prediction Based on Functional Network. Neural Process Lett 38, 305–320 (2013). https://doi.org/10.1007/s11063-012-9247-8
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DOI: https://doi.org/10.1007/s11063-012-9247-8