Extended Kalman Filter Based Delay Compensation for High-Precision UAV Time Synchronization

High-precision time synchronization in UAV networks is particularly challenging due to the motion of communication nodes, as time synchronization depends on the measurement of the distance between nodes. Existing studies on time synchronization mainly focus on static networks, and relatively few involve wireless dynamic networks, such as flying networks. This paper introduces a delay-compensated model with two-way message passing for high-precision UAV Time Synchronization. A tracking algorithm based on the Extended Kalman Filter (EKF) is proposed to track the dynamic distance between the slave and master nodes and the clock drift of the slave node relative to the master node. The algorithm features low computational complexity and can handle uniform relative acceleration. The Mean Square Error (MSE) and Posterior Cramér-Rao Bound (PCRB) are used as performance metrics to evaluate the proposed method. Simulation confirms the method’s effectiveness in improving synchronization accuracy in dynamic environments.