室内BLE/MEMS跨楼层融合定位算法

周牧; 王斌; 田增山; 张千坤

doi:10.11959/j.issn.1000-436x.2017076

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室内BLE/MEMS跨楼层融合定位算法

学术论文 | 更新时间：2024-06-05

- 室内BLE/MEMS跨楼层融合定位算法
- Indoor BLE and MEMS based multi-floor fusion positioning algorithm
- 通信学报 2017年38卷第5期页码：1-10
- 作者机构：
  
  1. 重庆邮电大学移动通信技术重庆市重点实验室，重庆 400065
  2. 天津师范大学天津市无线移动通信与无线电能传输重点实验室，天津 300387
- 作者简介：
  
  [ "周牧（1984-），男，重庆人，博士，重庆邮电大学教授，主要研究方向为无线定位技术、机器学习与人工智能、凸优化理论。" ]
  [ "王斌（1991-），男，重庆人，重庆邮电大学硕士生，主要研究方向为指纹定位技术、传感器定位技术、融合定位技术。" ]
  [ "田增山（1968-），男，河南固始人，博士，重庆邮电大学教授，主要研究方向为蜂窝网无线定位系统、个人通信、GPS 精密定位和姿态测量、数据压缩和数据融合。" ]
  [ "张千坤（1992-），男，河南固始人，重庆邮电大学硕士生，主要研究方向为室内定位技术。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61301126);国家自然科学基金资助项目;The National Natural Science Foundation of China(61471077);长江学者和创新团队发展计划基金资助项目;The Program for Changjiang Scholars and Innovative Research Team in University(IRT1299);重庆市科委重点实验室专项经费基金资助项目;Special Fund of Chongqing Key Laboratory (CSTC);重庆市基础与前沿研究计划基金资助项目（重点）;Fundamental and Frontier Research Project of Chongqing (Key Project)(cstc2015jcyjBX0065);重庆市高校优秀成果转化基金资助项目;University Outstanding Achievement Transformation Project of Chongqing(KJZH17117)
- DOI：10.11959/j.issn.1000-436x.2017076
  中图分类号： TP391
- 网络出版日期：2017-05，
  
  纸质出版日期：2017-05-25
- 稿件说明：
移动端阅览
周牧, 王斌, 田增山, 等. 室内BLE/MEMS跨楼层融合定位算法[J]. 通信学报, 2017,38(5):1-10.

Mu ZHOU, Bin WANG, Zeng-shan TIAN, et al. Indoor BLE and MEMS based multi-floor fusion positioning algorithm[J]. Journal on communications, 2017, 38(5): 1-10.
周牧, 王斌, 田增山, 等. 室内BLE/MEMS跨楼层融合定位算法[J]. 通信学报, 2017,38(5):1-10. DOI： 10.11959/j.issn.1000-436x.2017076.

Mu ZHOU, Bin WANG, Zeng-shan TIAN, et al. Indoor BLE and MEMS based multi-floor fusion positioning algorithm[J]. Journal on communications, 2017, 38(5): 1-10. DOI： 10.11959/j.issn.1000-436x.2017076.

摘要

提出一种基于微机电系统（MEMS

micro electro mechanical system）传感器与低功耗蓝牙(BLE

bluetooth low energy)数据融合的室内 BLE/MEMS 跨楼层定位算法。首先利用仿射传播聚类、离群点检测和接收信号强度（RSSI

received signal strength indicator）滤波算法对指纹库进行去噪，然后采用扩展卡尔曼滤波器，并根据抗差M估计方法对二维目标位置进行最优估计，最后基于气压计输出和地理位置信息实现对目标的高度估计。实验结果表明，该系统在室内环境下能够达到水平和垂直定位均方根误差小于0.7 m和0.35 m的跨楼层融合定位。

Abstract

Based on the data fusion from micro electro mechanical system (MEMS) sensors and low-power bluetooth (BLE)

an indoor BLE and MEMS based multi-floor positioning algorithm was proposed.First of all

the affinity propagation clustering

outlier detection and received signal strength indicator (RSSI) filtering algorithms were applied to denoise the fingerprint database.Second

by using the extended Kalman filter

the robust M estimation algorithm was used to perform the optimal estimation of the two-dimensional target position.Finally

the barometer output and geographical position information was considered to realize the height estimation of the target.The experimental results show that the proposed system is able to achieve the horizontal and vertical positioning errors lower than 0.7 m and 0.35 m respectively in multi-floor fusion positioning.

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references

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