Outlier detection based on variance estimation for satellite clock offset and its application in Galileo HAS service

Outlier detection and mitigation in satellite clock offsets are prerequisites for ensuring high-precision positioning and timing services. This paper proposes a quartile-based variance estimation method dedicated to satellite clock offset outlier detection. A systematic theoretical analysis and robustness evaluation, based on the breakdown point and influence function, are conducted and compared with the commonly used median-based and Allan variance methods. Simulation experiments reveal that the quartile-based method achieves superior accuracy with higher computational efficiency under low anomaly contamination, while the median-based method is recommended for high-anomaly scenarios. The real-time clock offset data of high accuracy service (HAS) from Galileo are used to validate the outlier detection performance of the methods, and the results show both quartile-based and median-based methods achieve rapid and stable convergence, significantly outperforming sample-based and Allan variance approaches. Precise Point Positioning (PPP) experiments further confirm that the accuracy of horizontal PPP has significantly improved in the N-direction and E-direction, with enhancement magnitudes reaching 10%-30% in some cases based on robust variance estimation methods. However, in the U-direction, the improvement in accuracy is limited.