Many applications involving the use of drones in sensor networks require precise synchronization from the involved sensors. However, not many papers evaluate the precision of the synchronism that can be obtained by means of exchanging packets in mobile sensor networks. This lack can be explained by the difficulties encountered in modeling the swift movements of the drones and the large volumes of these elements in a monitored area. Measuring phase noise also requires techniques that are quite different from those commonly used to analyze data networks. This paper suggests a simulation model based on discrete events, deployed in a Matlab Simulink® tool, which combines calculating loss probability in a mobile sensor network with measuring phase error between the sensor clock and the reference clock. Phase error is evaluated by Maximum Time Interval Error (MTIE) and Allan Deviation (ADEV) statistics. Results show that synchronism precision is strongly connected to the probability of message loss and that, with fewer losses, precision in the order of tens of nano-seconds can be obtained.

许多涉及在传感器网络中使用无人机的应用都需要相关传感器的精确同步。然而，很少有论文评估通过在移动传感器网络中交换数据包可以获得的同步精度。这种缺乏可以通过在建模无人机的快速移动时遇到的困难以及在监控区域中大量这些元素来解释。测量相位噪声还需要与通常用于分析数据网络的技术完全不同的技术。本文提出了一种基于离散事件的仿真模型，该模型部署在 Matlab Simulink® 工具中，该模型将计算移动传感器网络中的丢失概率与测量传感器时钟和参考时钟之间的相位误差相结合。相位误差由下式评估最大时间间隔误差(MTIE) 和艾伦偏差(ADEV) 统计。结果表明，同步精度与消息丢失的概率密切相关，在丢失较少的情况下，可以获得数十纳秒级的精度。