Bluetooth Indoor Location Method based on Matrix Completion and Compressed Sensing

YANG Gang; CHAI Ya-wen

doi:10.13756/j.gtxyj.2019.05.012

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Bluetooth Indoor Location Method based on Matrix Completion and Compressed Sensing

- Bluetooth Indoor Location Method based on Matrix Completion and Compressed Sensing
- Study on Optical communication Issue 5, Pages: 58-63(2019)
- 作者机构：
  
  西安邮电大学通信与信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13756/j.gtxyj.2019.05.012
  CLC： TN925
- Published：2019，
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[1]杨刚,柴雅文.基于矩阵填充和压缩感知的蓝牙室内定位方法[J].光通信研究,2019(05):58-63.

YANG Gang, CHAI Ya-wen. Bluetooth Indoor Location Method based on Matrix Completion and Compressed Sensing. [J]. (5):58-63(2019)
[1]杨刚,柴雅文.基于矩阵填充和压缩感知的蓝牙室内定位方法[J].光通信研究,2019(05):58-63. DOI： 10.13756/j.gtxyj.2019.05.012.

YANG Gang, CHAI Ya-wen. Bluetooth Indoor Location Method based on Matrix Completion and Compressed Sensing. [J]. (5):58-63(2019) DOI： 10.13756/j.gtxyj.2019.05.012.

摘要

基于低功耗蓝牙的接收信号强度指纹定位方式

文章提出了一种无需采集过多数据点建立指纹数据库且能及时矫正定位误差的定位方法。该方法分为两个阶段

离线数据采集阶段

利用低秩矩阵填充理论恢复只有少量采集点的指纹数据库

减小前期工作量;在线数据匹配阶段

对指纹数据库进行聚类匹配后

将定位问题转化为压缩感知模型

提高定位精确度。对用户在线阶段的实时数据进行均方根操作、反距离权重插值矫正和完善指纹库。实验结果表明

提出的定位算法能够有效减少40%左右的前期数据采集工作量

并将定位误差由0.93 m减小至0.71 m。

Abstract

In order to achieve fingerprint location based on the strength of low energy bluetooth received signal

a new fingerprint location method is proposed

which does not need to collect too many data points to establish fingerprint database and can correct the positioning error in time. In the off-line phase

we use the low rank matrix completion theory to recover the fingerprint database with only a small number of acquisition points to reduce the workload. In the online stage

after clustering and matching the fingerprint database

the localization problem is transformed into compressed sensing model to improve positioning accuracy. Experimental results show that the proposed positioning algorithm can effectively reduce about 40% workload of early data acquisition and reduce the positioning error from 0.93 m to 0.71 m.

关键词

室内定位低功耗蓝牙矩阵填充压缩感知反距离插值

Keywords

indoor locationbluetooth low energymatrix completioncompressed sensinginverse distance weighted

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