Real-time Satellite Clock Products Research Articles

A Real-Time Linear Prediction Algorithm for Detecting Abnormal BDS-2/BDS-3 Satellite Clock Offsets

Due to space environment interference, imperfect data processing model, and the performance of atomic clocks, real-time satellite clock products often contain outliers or irregular biases. We propose a real-time linear moving short-term prediction algorithm to predict clock offsets and detect abnormalities. The proposed algorithm mainly includes phase/frequency anomaly detection and real-time prediction part. Both the phase and frequency domains are used to detect abnormal clock offsets with previous epochs for building the clock prediction model accurately. The real-time moving prediction module utilizes the high short-term prediction performance to check the clock abnormality. The performance of the algorithm is then evaluated for all satellites with real-time estimated satellite clock offsets. To verify the feasibility and effectiveness of the proposed linear moving model and algorithm, the results of the grey model GM(1,1) and the ARIMA model are also compared. The experimental results indicated that the algorithm can detect clock outliers, frequency modulation, and phase jumps, and the linear model has a better clock performance improvement. After the abnormalities are removed with the proposed algorithm, the average STD accuracy of the real-time clock offsets for all satellites is improved by 15.5%, compared to an improvement of 11.4% by the GM(1,1) model and 11.5% by the ARIMA model. The PPP results demonstrate that the proposed clock prediction algorithm improves the positioning accuracy by 8.1%, 13.3%, and 16.9% in the east, north, and up components, respectively.

Real-time clock prediction of multi-GNSS satellites and its application in precise point positioning

With the development of Global Navigation Satellite System (GNSS), multi-GNSS is expected to greatly benefit precise point positioning (PPP), especially during the outage of real time service (RTS). In this paper, we focus on the performance of multi-GNSS satellite clock prediction and its application in real-time PPP. Based on the statistical analysis of multi-system satellite clock products, a model consisting of polynomial and periodic terms is employed for multi-system satellite clock prediction. To evaluate the method proposed, both post-processed and real-time satellite clock products are employed in simulated real-time processing mode. The results show that the accuracy of satellite clock prediction is related to atomic clock type and satellite type. For GPS satellites, the average standard deviations (STDs) of Cs atomic clocks will reach as high as 0.65 ns while the STD of Rb atomic clocks is only about 0.15 ns. As for BDS and Galileo, the average STD of 2-hour satellite clock prediction are 0.30 ns and 0.06 ns, respectively. In addition, it is validated that real-time PPP can still achieve positioning accuracy of one to three decimeters by using products of 2-hour satellite clock prediction. Moreover, compared to the results of GPS-only PPP, multi-system can greatly enhance the accuracy of real-time PPP from 12.5% to 18.5% in different situations.