基于频率响应的FTTR WLAN室内无线定位算法研究

龙智丰; 张靖

doi:10.11959/j.issn.2096-3750.2023.00355

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基于频率响应的FTTR WLAN室内无线定位算法研究

专题：短距无线通信技术 | 更新时间：2024-08-16

- 基于频率响应的FTTR WLAN室内无线定位算法研究
- Research on FTTR WLAN indoor wireless location algorithm based on frequency response
- 物联网学报 2023年7卷第3期页码：72-84
- 作者机构：
  
  1. 华中科技大学电子信息与通信学院，湖北武汉 430074
  2. 华中科技大学绿色通信与网络国际联合研究中心，湖北武汉 430074
- 作者简介：
  
  [ "龙智丰（2000- ），男，华中科技大学电子信息与通信学院硕士生，主要研究方向为无线通信、室内定位" ]
  [ "张靖（1975- ），男，博士，华中科技大学电子信息与通信学院副教授，主要研究方向为无线通信、绿色通信、短距接入网络、光网络和无线网络融合、下一代通信网络等" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(U2001210);国家重点研发计划;The National Key Research and Development Program of China(2020YFB1806605);湖北省重点研发计划;The Key Research and Development Program of Hubei Province(2021BAA009)
- DOI：10.11959/j.issn.2096-3750.2023.00355
  中图分类号： TN929.5
- 纸质出版日期：2023-09-30，
  
  网络出版日期：2023-09，
- 稿件说明：
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龙智丰, 张靖. 基于频率响应的FTTR WLAN室内无线定位算法研究[J]. 物联网学报, 2023,7(3):72-84.

ZHIFENG LONG, JING ZHANG. Research on FTTR WLAN indoor wireless location algorithm based on frequency response. [J]. Chinese journal on internet of things, 2023, 7(3): 72-84.
龙智丰, 张靖. 基于频率响应的FTTR WLAN室内无线定位算法研究[J]. 物联网学报, 2023,7(3):72-84. DOI： 10.11959/j.issn.2096-3750.2023.00355.

ZHIFENG LONG, JING ZHANG. Research on FTTR WLAN indoor wireless location algorithm based on frequency response. [J]. Chinese journal on internet of things, 2023, 7(3): 72-84. DOI： 10.11959/j.issn.2096-3750.2023.00355.

摘要

高精度和可靠的室内无线定位服务已经被广泛使用，为了获得良好的定位精度，定位算法的设计需要与无线定位设施相匹配。全屋光纤（FTTR

fiber to the room）是基于新一代无线局域网（WLAN

wireless local area network）标准IEEE 802.11 ax所开发的室内接入网络方案。相较于已有的Wi-Fi网络，FTTR可用频带宽度大大增加，同时FTTR WLAN也缺乏支持定位功能的公共有效数据集，这使得基于FTTR WALN场景的定位研究面临巨大障碍。为了解决上述问题，首先，提出基于频率响应的FTTR WLAN场景数据集生成方法，利用已有的Wi-Fi定位数据集生成FTTR可用频带宽度内的频率响应矩阵；然后，提出利用并行路径的主成分分析（PCA

principal component analysis）的方法生成分类矩阵，并利用全连接神经网络对生成的数据集进行训练来提高精度。在真实测量数据集上的实验结果表明，所提定位算法可以达到误差小于1 m的定位精度，不仅比传统位置估计算法精度更高，而且基本达到了实际应用的细粒度定位要求。

Abstract

Highly accurate and reliable indoor wireless positioning services have been widely used.In order to obtain good positioning accuracy

the design of positioning algorithms needs to be matched with wireless positioning facilities.fiber to the room (FTTR) is an indoor access network solution based on IEEE 802.11 ax

a new generation of wireless local area network (WLAN) standard.Compared with the existing Wi-Fi networks

FTTR has a much larger available band width.However

FTTR WLAN also lacks of a public valid data set to support localization functions

which makes the localization research based on FTTR scenarios face huge obstacles.In order to solve the above problems

firstly

a frequency response-based FTTR scene dataset generation method was proposed

which uses the existing Wi-Fi localization dataset to generate the frequency response matrix within the available band width of FTTR.Then

the parallel path principal component analysis (PCA) method was used to generate the classification matrix.And the generated dataset was trained using a fully connected neural network to improve the accuracy.The experimental results on the real measurement dataset show that the proposed localization algorithm can achieve a localization accuracy of less than 1 m

which is not only more accurate than the traditional location estimation algorithm

but also basically meets the fine-grained localization requirements for practical applications.

关键词

全屋光纤数据集合成主成分分析

Keywords

FTTRdataset synthesisprincipal component analysis

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