LAUSR

Due to the unique merits of unmanned aerial vehicle (UAV) systems, they have already been harnessed for military, public, and civil applications. Time synchronization is a significant premise of formatting and applying UAV networks. However, the irregular high-speed mobile UAVs pose new challenges to time synchronization, especially when external time references are unavailable in some rigid scenarios. Therefore, in these harsh cases, self-time-synchronization (STS) without any external assistance should be concerned to overcome the relative velocity between UAVs caused by irregular high-speed motion. In this paper, a realistic timestamps model for the multi-UAV networks is established, and then a dynamic topology-based maximum likelihood estimator will be developed to carry out the STS. Furthermore, by introducing the information on frequency offset, a new estimator with the closed-form expression is proposed based on a two-way message exchange framework. After that, a tracking algorithm with the assistance of estimation results will be introduced to compensate for the time-varying change of the clock parameters for the dynamic topology UAV networks. To evaluate the performance of the estimator, both the estimation error and Cramér-Rao lower bound are analyzed. Numerical results show that the proposed algorithm exhibits its superiority in STS performance and computational complexity compared to the existing two-way message exchange algorithm using timestamps only.