传感技术学报2017，Vol.30Issue(2)：284-290,7.DOI:10.3969/j.issn.1004-1699.2017.02.020
基于LQI权重和改进粒子群算法的室内定位方法
The Indoor Localization Based on LQI weight and ImprovedParticle Swarm Optimization Algorithm
摘要
Abstract
In order to solve the positioning error caused by non line-of-sight and multipath transmission in indoor location of wireless sensor networks,particle swarm optimization algorithm based on trigonometric is proposed.In view of the range error caused by RSSI fluctuation,this paper uses relationship between LQI and RSSI to optimize the RSSI value,and puts forward RSSI ranging algorithm based on LQI weight.Compared to the standard particle swarm optimization algorithm,the improved algorithm improves the weight model and the velocity update strategy,which avoids the local optimal value.After the simulation experiment,it is further applied to the Zigbee platform positioning experiment.The results show that the proposed algorithm has higher accuracy compared to the traditional ranging and positioning algorithm,which average localization error is less than 0.5m.关键词
室内定位/衰减模型/粒子群算法/RSSI/LQIKey words
indoor localization/attenuation model/particle swarm optimization algorithm/RSSI/LQI分类
信息技术与安全科学引用本文复制引用
尚俊娜,盛林,程涛,施浒立,岳克强..基于LQI权重和改进粒子群算法的室内定位方法[J].传感技术学报,2017,30(2):284-290,7.基金项目
浙江省自然科学基金青年基金项目(LQ13F010010) （LQ13F010010）
浙江省重点科技创新团队"固态存储和数据安全关键技术创新团队"项目(2013TD03) （2013TD03）
浙江省"电子科学与技术"重中之重学科开放基金项目(GK13020320003/004) （GK13020320003/004）
