Abstract
The satellite clocks used in the BeiDou-2 satellite navigation System (BDS) are Chinese self-developed Rb atomic clocks, and their performances and stabilities are worse than GPS and Galileo satellite clocks. Due to special periodic noises and nonlinear system errors existing in the BDS clock offset series, the GPS ultra-rapid clock model, which uses a simple quadratic polynomial plus one periodic is not suitable for BDS. Therefore, an improved prediction model for BDS satellite clocks is proposed in order to enhance the precision of ultra-rapid predicted clock offsets. First, a basic quadratic polynomial model which is fit for the rubidium (Rb) clock is constructed for BDS. Second, the main cyclic terms are detected and identified by the Fast Fourier Transform (FFT) method according to every satellite clock offset series. The detected results show that most BDS clocks have special cyclic terms which are different from the orbit periods. Therefore, two main cyclic terms are added to absorb the periodic effects. Third, after the quadratic polynomial plus two periodic fitting, some evident nonlinear system errors also exist in the model residual, and the Back Propagation (BP) neural network model is chosen to compensate for these nonlinear system errors. The simulation results show that the performance and precision using the improved model are better than that of China iGMAS ultra-rapid prediction (ISU-P) products and the Deutsches GeoForschungsZentrum GFZ BDS ultra-rapid prediction (GBU-P) products. Comparing to ISU-P products, the average improvements using the proposed model in 3 h, 6 h, 12 h and 24 h are 23.1%, 21.3%, 20.2%, and 19.8%, respectively. Meanwhile the accuracy improvements of the proposed model are 9.9%, 13.9%, 17.3%, and 21.2% compared to GBU-P products. In addition, the kinematic Precise Point Positioning (PPP) example using 8 Multi-GNSS Experiment MGEX stations shows that the precision based on the proposed clock model has improved about 16%, 14%, and 38% in the North (N), East (E) and Height (H) components.
Highlights
The precision of real-time satellite clock products has a direct impact on the capability of the Global Navigation Satellite System (GNSS) Position, Navigation, and Timing (PNT) service [1,2,3,4,5,6,7].In the case of multi-GNSS PNT, the performances of Chinese BeiDou-2 satellite navigation System (BDS) satellite clocks are no match for that of GPS and Galileo
The accuracy improvements of the proposed model are 9.9%, 13.9%, 17.3%, and 21.2% compared to GFZ BDS ultra-rapid prediction (GBU-P) products
An improved prediction model for BDS satellite clocks is proposed in order to enhance the accuracies of ultra-rapid predicted clock offsets
Summary
The precision of real-time satellite clock products has a direct impact on the capability of the Global Navigation Satellite System (GNSS) Position, Navigation, and Timing (PNT) service [1,2,3,4,5,6,7]. The second category are the Beidou ultra-rapid clock offset products, which are based on 24-h clock offset observations for real-time forecasting of 24-h clock offsets. In the previous research of real-time clock prediction, GPS clock offset predictions in the IGS ultra-rapid products were modeled by a quadratic polynomial plus one period [14]. Huang used the improved model to predict the IGS ultra-rapid clock offset of GPS, but the model does not consider the nonlinear colored noise [9,26]. In order to improve the precision of real-time clock offset prediction, the satellite clock noise type, period characteristics, frequency stability, and the physical model have been researched [9,10,13,15]. Based on ISU and GBU clock offset observations, the numerical examples are designed to demonstrate the accuracy and effectiveness of the improved model
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
