哈尔滨工程大学学报2023，Vol.44Issue(11)：1996-2004,9.DOI:10.11990/jheu.202309051
基于因子图模型的水下传感器网络时间同步方法
Time synchronization method for underwater sensor networks based on the factor graph model
摘要
Abstract
To address the problems of lengthy synchronization and low efficiency in underwater sensor networks,a parameter fusion method based on the factor graph model is proposed in this article for measuring underwater loca-tion,sound speed,and time delay.After calculating the marginal probability density function of system clock bias parameters,it is simplified through binarization;thus,the clock bias parameters of each sensor can be quickly calculated,enabling dynamic time synchronization across the network.Experimental results demonstrate that under the assumption of high synchronization accuracy of larger than 8×10-4 s,the synchronization period is only half the current methods,and the time setting of the entire network can be achieved within one cycle,reducing computa-tional load.关键词
概率图模型/因子图模型/水下时间同步方法/水下授时/水下传感器网络/和积算法/概率密度函数/全局函数Key words
probabilistic graph model/factor graph model/underwater time synchronization method/underwater timekeeping/underwater sensor network/sum-product algorithm/probability density function/global function分类
测绘与仪器引用本文复制引用
孙大军,欧阳雨洁,韩云峰,王泽彧,刘璐..基于因子图模型的水下传感器网络时间同步方法[J].哈尔滨工程大学学报,2023,44(11):1996-2004,9.基金项目
国家重点研发计划(2021YFC2801300) （2021YFC2801300）
黑龙江省自然科学基金项目(YQ2019D003). （YQ2019D003）
