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http://dx.doi.org/10.11003/JPNT.2020.9.4.397

Outlier Detection Method for Time Synchronization  

Lee, Young Kyu (Center for Time and Frequency Metrology, Korea Research Institute of Standards and Science)
Yang, Sung-hoon (Center for Time and Frequency Metrology, Korea Research Institute of Standards and Science)
Lee, Ho Seong (Center for Time and Frequency Metrology, Korea Research Institute of Standards and Science)
Lee, Jong Koo (Center for Time and Frequency Metrology, Korea Research Institute of Standards and Science)
Lee, Joon Hyo (Center for Time and Frequency Metrology, Korea Research Institute of Standards and Science)
Hwang, Sang-wook (Center for Time and Frequency Metrology, Korea Research Institute of Standards and Science)
Publication Information
Journal of Positioning, Navigation, and Timing / v.9, no.4, 2020 , pp. 397-403 More about this Journal
Abstract
In order to synchronize a remote system time to the reference time like Coordinated Universal Time (UTC), it is required to compare the time difference between the two clocks. The time comparison data may have some outliers and the time synchronization performance can be significantly degraded if the outliers are not removed. Therefore, it is required to employ an effective outlier detection algorithm for keeping high accurate system time. In this paper, an outlier detection method is presented for the time difference data of GNSS time transfer receivers. The time difference data between the system time and the GNSS usually have slopes because the remote system clock is under free running until synchronized to the reference clock time. For investigating the outlier detection performance of the proposed algorithm, simulations are performed by using the time difference data of a GNSS time transfer receiver corrected to a free running Cesium clock with intentionally inserted outliers. From the simulation, it is investigated that the proposed algorithm can effectively detect the inserted outliers while conventional methods such as modified Z-score and adjusted boxplot cannot. Furthermore, it is also observed that the synchronization performance can be degraded to more than 15% with 20 outliers compared to that of original data without outliers.
Keywords
outlier detection; synchronization; modified Z-score; GNSS; system time;
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