Distributed Clock Parameter Tracking for Highly Dynamic Multi-UAV Networks-Enabled Industrial IoT

With the increasing demands of the Industrial Internet of Things (IIoT), highly dynamic multi-unmanned aerial vehicle (UAV) networks are becoming indispensable to IIoT due to their flexibility, cost-effectiveness, robust safety measures, and real-time data collection capabilities. Accurate time synchronization is crucial for coordinated missions of multi-UAV networks, yet the time-varying nature of clock parameters and the rapid movements of UAVs pose significant challenges to achieving precise synchronization. This article introduces new state and observation models for clock and velocity parameters and proposes a Doppler and timestamp-based distributed algorithm for tracking clock parameters using the Kalman filter. To evaluate the performance of the proposed algorithm, we derive the Bayesian Cramer-Rao lower bound and conduct numerical simulations. The results of the simulations demonstrate that our algorithm surpasses existing methods in terms of accuracy in tracking clock parameters.