A Modified Strong Tracking Adaptive Kalman Filter for Precision Clock Synchronization System

Abstract

In order to reduce the clock offset caused by network delay jitter, network asymmetry, clock drift and clock frequency difference in the clock synchronization process of IEEE1588, a modified Strong Tracking Adaptive Kalman Filter (MSTAKF) algorithm was proposed. The Kalman filter model established by the algorithm is based on clock offset, network delay, frequency deviation and asymmetry ratio. The filter includes the modified strong tracking algorithm based on fuzzy logic and hypothesis test proposed in this paper, which can effectively eliminate the influence of outliers, and finally make the model tracking effect better. In addition, the modified Sage‐Husa algorithm based on Cholesky decomposition is also included, which makes the measurement noise more stable and ensures the positivity of the measurement noise covariance. The experimental results show that the proposed MSTAKF is smoother than Karman filter (KF), Sage‐Husa adaptive Kalman filter (AKF) and strong tracking Sage‐Husa adaptive Kalman filter (STAKF). Compared with these filter algorithms after testing in the LAN environment, the precision improvement and accuracy rate are significantly improved. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.