Time Synchronization Method for Connected Vehicles Based on Kalman Filter Time Offset Parameter Prediction

초록

With the continuous evolution of technology, vehicles have become intelligent devices that integrate information processing and transmission capabilities, and the time synchronization between vehicles is particularly important in the coordination process, which requires accurate and reliable time synchronization technology. In order to solve the problem of cooperative control inaccuracy caused by clock deviation and frequency offset of vehicle nodes in specific environments (such as GPS signal occlusion) in connected vehicles, this paper proposes a time-frequency parameter prediction time synchronization method based on improved Kalman filter, which is mainly aimed at the time synchronization requirements of vehicular networks in low- to mid-frequency collaborative control scenarios. By establishing a state space model of network delay, the clock deviation and frequency offset parameters are jointly estimated as the state quantities of the system. Combined with the Precision Time Protocol (PTP) protocol and the improved Kalman filter algorithm, the dynamic compensation mechanism is realized, which effectively solves the limitations of the traditional PTP method in the environment of limited hardware resources and network fluctuations. Experimental results show that the proposed method shows good effect in reducing clock offset, with a synchronization accuracy of sub-millisecond (average deviation of 0 & centerdot;574 ms), which is 93.6% and 79.2% optimized compared with the unsynchronized state and NTP synchronization, respectively, and has better stability (standard deviation 0 & centerdot;42 ms), which significantly improves the synchronization accuracy. The results of this study are of great significance for solving the problem of time synchronization of connected car clocks.

키워드