摘要
针对室内WiFi和蓝牙单独定位时定位精度较低的问题,提出基于多属性代价函数的WiFi与蓝牙总体最小二乘(TLS)融合定位算法。为减小接收信号强度指示(RSSI)值不稳定的信标节点造成的测距误差,采用WiFi/蓝牙多属性代价函数综合评估信标定位性能,优选出最佳信标节点参与融合定位。在定位解算中,同时考虑测距误差和信标节点部署误差。采用TLS算法对待定位节点进行最优位置估计,进一步提高定位精度。实验仿真结果表明:在RSSI噪声标准差为3 d Bm的条件下,算法定位精度优于1.9 m的概率可达95%,相比单独定位抗噪性能明显提高且定位误差显著降低。
Aiming at the problem of low localization precision of indoor WiFi and Bluetooth positioning separately,WiFi and Bluetooth total least squares（TLS） fusion localization algorithm based on multi-attribute cost function is proposed.In order to reduce the ranging error due to beacon node with instable RSSI,multi-attribute cost function is used to evaluate the positioning performance of beacon node comprehensively,and the optimal beacon nodes is selected to participate in fusion localization.Meanwhile consider the influence of the ranging error and beacon nodes deployment error in the positioning calculation,TLS algorithm is adopted to estimate the optimal position of unknown nodes for improving the localization precision.The simulation results show that the localization precision of the algorithm can reach 1.9 m with 95 % probability when RSSI noise standard deviation is 3 d Bm,anti-noise performance is obviously improved and localization error is significantly decreased compared with separate localization.
作者
关维国
邹林杰
郝德华
焦萌
GUAN Wei-guo;ZOU Lin-jie;HAO De-hua;JIAO Meng(College of Electronic and Information Engineering,Liaoning University of Technology,Jinzhou 121001,China)
出处
《传感器与微系统》
CSCD
2018年第11期132-135,138,共5页
Transducer and Microsystem Technologies
基金
辽宁省自然科学基金面上资助项目(20170540437)
关键词
无线局域网
蓝牙
多属性代价函数
总体最小二乘
融合定位
WiFi
Bluetooth
muhi-attribute cost function
total least squares（TLS）
fusion localization
作者简介
关维国（1973-），男，博士，教授，主要研究领域为移动网络定位、泛在网络无线定位，E—mail：guanwei8@gmail．coom.;邹林杰（1991-），女，硕士研究生，主要研究方向为移动通信与无线技术，E-mail：956834548@qq．com.
