The system time of the four major navigation satellite systems is mainly maintained by multiple high-performance atomic clocks at ground stations.This operational mode relies heavily on the support of ground stations....The system time of the four major navigation satellite systems is mainly maintained by multiple high-performance atomic clocks at ground stations.This operational mode relies heavily on the support of ground stations.To enhance the high-precision autonomous timing capability of next-generation navigation satellites,it is necessary to autonomously generate a comprehensive space-based time scale on orbit and make long-term,high-precision predictions for the clock error of this time scale.In order to solve these two problems,this paper proposed a two-level satellite timing system,and used multiple time-keeping node satellites to generate a more stable space-based time scale.Then this paper used the sparse sampling Long Short-Term Memory(LSTM)algorithm to improve the accuracy of clock error long-term prediction on space-based time scale.After simulation,at sampling times of 300 s,8.64×10^(4) s,and 1×10^(6) s,the frequency stabilities of the spaceborne timescale reach 1.35×10^(-15),3.37×10^(-16),and 2.81×10^(-16),respectively.When applying the improved clock error prediction algorithm,the ten-day prediction error is 3.16×10^(-10) s.Compared with those of the continuous sampling LSTM,Kalman filter,polynomial and quadratic polynomial models,the corresponding prediction accuracies are 1.72,1.56,1.83 and 1.36 times greater,respectively.展开更多
基金funded by the National Natural Science Foundation of China Youth Project (Grant No.12104485)funding support from the basic research project of Microsatellite Innovation Institute,Chinese Academy of Sciences with grant number JCZX2022B-03.
文摘The system time of the four major navigation satellite systems is mainly maintained by multiple high-performance atomic clocks at ground stations.This operational mode relies heavily on the support of ground stations.To enhance the high-precision autonomous timing capability of next-generation navigation satellites,it is necessary to autonomously generate a comprehensive space-based time scale on orbit and make long-term,high-precision predictions for the clock error of this time scale.In order to solve these two problems,this paper proposed a two-level satellite timing system,and used multiple time-keeping node satellites to generate a more stable space-based time scale.Then this paper used the sparse sampling Long Short-Term Memory(LSTM)algorithm to improve the accuracy of clock error long-term prediction on space-based time scale.After simulation,at sampling times of 300 s,8.64×10^(4) s,and 1×10^(6) s,the frequency stabilities of the spaceborne timescale reach 1.35×10^(-15),3.37×10^(-16),and 2.81×10^(-16),respectively.When applying the improved clock error prediction algorithm,the ten-day prediction error is 3.16×10^(-10) s.Compared with those of the continuous sampling LSTM,Kalman filter,polynomial and quadratic polynomial models,the corresponding prediction accuracies are 1.72,1.56,1.83 and 1.36 times greater,respectively.
