摘要
针对传统的超宽带(UWB)室内定位方法中,UWB信号极易被遮挡,满足不了3个以上有效测距信息,导致无法精确定位的问题,提出了一种基于接收信号强度(RSSI)辅助的精确测距混合定位算法。该算法通过对数正态模型,将无线网络(wireless LAN, WLAN)中测量的RSSI转换为距离信息,通过构建距离差的代价函数,结合单个UWB基站的精确测距,利用搜索方法,实现了在多个RSSI测量值辅助下,一个UWB测距基站便可完成精确定位。该算法与三边测量定位中的最小二乘估计算法和最大似然估计算法对比,定位精度在任意网络环境下均优于最小二乘估计算法,且在定位精度相似的情况下,计算量远少于最大似然估计算法。
In ultra-wideband (UWB)-based indoor positioning, the number of base stations used for location calculating is always affected by non-line-of-sight (NLOS) propagation or sheltering, and thus leading to no solution of location equations. This paper proposes a precise indoor localization algorithm based on received signal strength indicator (RSSI) and UWB ranging techniques. The multiple RSSI measurements of wireless local area network (WLAN) is transformed into the corresponding distances, which can be used to improve the positioning accuracy of the UWB. Our technique can localize targets by minimizing the positioning errors with only one UWB base station. Compared with the existing least squares (LS) and maximization likelihood (ML) algorithms, our method achieves better performances in arbitrary structure of base stations with low computational complexity.
作者
段林甫
秦爽
万群
DUAN Lin-fu;QIN Shuang;WAN Qun(School of Information and Communication Engineering,University of Electronic Science and Technology of China Chengdu 611731;School of Physics and Electronic Engineering,Sichuan Normal University Chengdu 610101)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2019年第3期331-335,共5页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(61771316)
四川省科学基金应用基础项目(2018JY0218)
四川省教育厅青年基金(14ZB003)
关键词
混合定位
室内定位
对数正态模型
低密度布站
三边测量
hybrid location
indoor position
lognormal model
low density station distribution
trilateration
