Abstract
GNSS compatibility and interoperability is one of the most significant problems in multi-system navigation and position. The precise prediction of system time offset is one of the most important problems for application of GNSS compatibility and interoperability. To increase the prediction precision of system time offset and meet the requirement of multi-system users, this essay studies the prediction algorithm of system time offset. First, based on research on the prediction principle of end-point (EP) and Kalman filter, the feature of GNSS system time offset is analyzed. The initial values of Kalman filter parameters are determined to reduce the uncertainty and error caused by it. In addition, the real-time measurement data is provided by a platform that monitors GNSS system time offset at National Time Service Center (NTSC). It verifies the applicability of two methods to predict the system time offset and compares the precision of EP and Kalman filter. The result shows that for any type data of system time offset, when real-time precision prediction is required, Kalman filter provides higher precision and will be influenced less significantly by other factors: For GPS data, precision is about 1 ns and for GLONASS data, it is 2 ns. It is 0.5 times higher than that of EP. In other cases, EP is more precise.
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Acknowledgments
Funded by the National Natural Science Foundation of China (Grant No. 11503030) and the State Key Laboratory of Geo-information Engineering, No. SKLGIE2014-M-2-5.
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Zhu, L., Zhang, H., Li, X., Ren, Y., Xu, L. (2016). Analyzing Prediction Methods and Precision of GNSS System Time Offset Using End-Point and Kalman Filter. In: Sun, J., Liu, J., Fan, S., Wang, F. (eds) China Satellite Navigation Conference (CSNC) 2016 Proceedings: Volume III. Lecture Notes in Electrical Engineering, vol 390. Springer, Singapore. https://doi.org/10.1007/978-981-10-0940-2_58
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DOI: https://doi.org/10.1007/978-981-10-0940-2_58
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