沈阳航空航天大学学报2024，Vol.41Issue(2)：57-67,11.DOI:10.3969/j.issn.2095-1248.2024.02.007
基于最大熵模糊概率数据关联的室内定位算法
Indoor location algorithm based on maximum entropy fuzzy probability data association
摘要
Abstract
Wireless sensor network is composed of multiple micro-sensor nodes,and positioning tech-nology is one of the important applications of WSN.At present,many localization algorithms have high localization accuracy in line of sight(LOS)environment,but poor localization accuracy in non-line-of-sight(NLOS)environment.An improved maximum entropy fuzzy probability data association algorithm based on arrival time was proposed.The grouping idea was utilized to divide N measure-ment values into L groups,and each group obtained the corresponding mobile node position estima-tion,model probability and covariance matrix through the interactive multi model(IMM)algorithm.Afterwards,the obtained L position estimation was subjected to non-line-of-sight detection through a validation gate.The position estimation contaminated by non line of sight errors was discarded,and the corresponding correlation probabilities was used to weight the correct position estimates to obtain the fi-nal position estimation.Simulation and experimental results show that the proposed algorithm can re-duce the influence of non line of sight errors and achieve higher positioning accuracy than the existing methods.关键词
无线传感器网络/室内定位/非视距/最大熵模糊概率/数据关联/到达时间Key words
wireless sensor network/indoor positioning/non-line-of-sight/maximum entropy fuzzy probability/data association/time of arrival分类
信息技术与安全科学引用本文复制引用
李轩,徐诗佳,王尔申..基于最大熵模糊概率数据关联的室内定位算法[J].沈阳航空航天大学学报,2024,41(2):57-67,11.基金项目
国家自然科学基金(项目编号:62173237) （项目编号:62173237）
辽宁省科技厅重点研发计划项目(项目编号:2020JH2/10100045) （项目编号:2020JH2/10100045）
