author：Huijie Xue , Wenfeng Nie, Tianhe Xu, Mowen Li, Yuguo Yang, Zhenlong Fang,Fan Gao

来源出版物：Measurement 文献号：https://doi.org/10.1016/j.measurement.2022.111998 出版年份：October 2022

abstract：Highly stable time reference is fundamental and significant for positioning, navigation and timing. The highprecision products generated by the international Global Navigation Satellite System Monitoring and Assessment Service (iGMAS) are currently based on the Global Positioning System time scale (GPST); however, the

daily GPST calibration process of iGMAS can introduce daily discontinuity that affects product stability and limits the accuracy of time and frequency transmissions. We aim to establish an internal time reference for iGMAS in this study, to make the products more independent and stable. Firstly, we optimize the commonly used

Kalman Plus Weights (KPW) algorithm by adding an exponential filter. The feasibility of the exponential filter to the KPW algorithm is analyzed in detail. Based on the optimized KPW algorithm, we then select 20 satellite-borne atomic clocks with better stability from the different GNSS systems to generate the free iGMAS time scale (iGMAST). After that, we steer the free iGMAST to Coordinated Universal Time (UTC). Finally, the performance of steered iGMAST and GPST are compared and analyzed. The results validate that the optimized KPW algorithm can improve the short-term stability of the time scale by an average of about 16 %. As a consequence, the stability of the established free iGMAST is better than that of a single atomic clock. For the steering process, the steering error of the iGMAST is controlled within ± 4 ns. On the whole, comparing to the GPST, the stability of the steered iGMAST is better when the averaging time is within the range of 2–40 days. For different averaging times, the stability of iGMAST is almost equivalent to that of GPST.

keywords：Time scale， iGMAS， KPW algorithm，Steering，Frequency stability，Exponential filter

citation：Xue, H., Nie, W., Xu, T., Li, M., Yang, Y., Fang, Z., & Gao, F. (2022). Establishment of iGMAST Based on Spaceborne Atomic Clocks by Optimizing Kalman Plus Weights Algorithm.Measurement, 111998.