WiFi and Bluetooth TLS fusion localization algorithm based on multi-attribute cost function

GUAN Wei-guo; ZOU Lin-jie; HAO De-hua; JIAO Meng

doi:10.13873/j.1000-9787(2018)11-0132-04

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WiFi and Bluetooth TLS fusion localization algorithm based on multi-attribute cost function

更新时间：2025-09-11

- WiFi and Bluetooth TLS fusion localization algorithm based on multi-attribute cost function
- Vol. 37, Issue 11, Pages: 132-135+138(2018)
- 作者机构：
  
  辽宁工业大学电子与信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-9787(2018)11-0132-04
  CLC： TN92
- Published：2018
- 稿件说明：
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[1]关维国,邹林杰,郝德华,焦萌.基于多属性代价函数的WiFi与蓝牙TLS融合定位算法[J].传感器与微系统,2018,37(11):132-135+138.

GUAN Wei-guo, ZOU Lin-jie, HAO De-hua, et al. WiFi and Bluetooth TLS fusion localization algorithm based on multi-attribute cost function[J]. 2018, 37(11): 132-135+138.
[1]关维国,邹林杰,郝德华,焦萌.基于多属性代价函数的WiFi与蓝牙TLS融合定位算法[J].传感器与微系统,2018,37(11):132-135+138. DOI： 10.13873/j.1000-9787(2018)11-0132-04.

GUAN Wei-guo, ZOU Lin-jie, HAO De-hua, et al. WiFi and Bluetooth TLS fusion localization algorithm based on multi-attribute cost function[J]. 2018, 37(11): 132-135+138. DOI： 10.13873/j.1000-9787(2018)11-0132-04.

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。

Abstract

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.

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references

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