Adaptive Kalman filter-based time synchronization algorithm for civil aviation communication

Abstract The traditional synchronization algorithms often struggle to meet the stringent requirements of civil aviation communication. This paper proposes an adaptive time synchronization algorithm based on Kalman filtering (KF) to enhance the synchronization performance of civil aviation communication systems. Firstly, a dynamic clock model is established considering the characteristics of civil aviation communication, with clock offset and drift as state variables. Moreover, a step-by-step detection strategy is employed to adaptively adjust the detection range based on the statistical characteristics of synchronization errors, thereby improving the algorithm’s robustness and convergence speed. To evaluate the algorithm’s performance, a civil aviation communication system-level simulation platform is built based on ICAO standards, and various typical scenarios, such as take-off, landing, and cruising, are designed. Simulation results demonstrate that the proposed algorithm achieves significant improvements in synchronization accuracy, convergence speed, and robustness compared to classical synchronization algorithms based on phase-locked loops (PLL) and early late gates (ELD).