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

With advances in technology, vehicles have evolved into intelligent systems capable of information processing and communication. Accurate and reliable time synchronization is crucial for coordination among connected vehicles. 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. 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.