基于Mann-Whitney秩和检验的无线局域网室内映射与定位方法

周牧; 王烟濛; 袁慧; 田增山

doi:10.11999/JEIT180392

基于Mann-Whitney秩和检验的无线局域网室内映射与定位方法

doi: 10.11999/JEIT180392

重庆邮电大学通信与信息工程学院重庆 400065

基金项目: 国家自然科学基金(61771083, 61704015)，重庆市研究生科研创新项目(CYS17221, CYS18240)，长江学者和创新团队发展计划(IRT1299)，重庆市科委重点实验室专项经费，重庆市基础与前沿研究计划基金资助项目（cstc2017jcyjAX0380，cstc2015jcyjBX0065），重庆市高校优秀成果转化(KJZH17117)

详细信息

作者简介:
周牧：男，1984年生，教授，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

王烟濛：女，1994年生，硕士生，研究方向为室内WLAN定位技术、定位性能评估技术

袁慧：女，1994年生，硕士，研究方向为室内Wi-Fi定位技术、定位网络优化

田增山：男，1968年生，教授，博士生导师，研究方向为移动通信、个人通信、GPS及蜂窝网定位技术

通讯作者:
王烟濛　hiwangym@gmail.com

中图分类号: TN929.5
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- 被引次数: 0
出版历程
- 收稿日期: 2018-04-26
- 修回日期: 2019-03-08
- 网络出版日期: 2019-03-28
- 刊出日期: 2019-07-01

Mann-Whitney Rank Sum Test Based Wireless Local Area Network Indoor Mapping and Localization Approach

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61771083, 61704015), The Postgraduate Scientific Research and Innovation Project of Chongqing (CYS17221, CYS18240), The Program for Changjiang Scholars and Innovative Research Team in University (IRT1299), The Fundamental and Frontier Research Project of Chongqing (cstc2017jcyjAX0380, cstc2015jcyjBX0065), The University Outstanding Achievement Transformation Project of Chongqing (KJZH17117)

摘要

摘要: 该文提出一种基于Mann-Whitney秩和检验的无线局域网(WLAN)室内映射与定位方法。该方法首先根据实际定位精度需求对目标区域中的运动路径进行分段，同时基于Mann-Whitney秩和检验方法合并相似运动路径片段；然后，利用一种基于相似接收信号强度(RSS)序列片段的信号聚类算法，保证同一聚类中RSS样本的物理邻接关系；最后，通过骨干节点的扩散映射，建立物理与信号空间的映射关系，实现对运动用户的定位。实验结果表明，相比于已有WLAN室内映射与定位方法，该文方法在无需运动传感器辅助和构建位置指纹数据库的条件下，能够实现更高的映射与定位精度。
- 无线局域网 /
- 室内定位 /
- 行为分析 /
- Mann-Whitney秩和检验 /
- 空间映射
Abstract: The Mann-Whitney rank sum test based Wireless Local Area Network (WLAN) indoor mapping and localization approach is proposed. Firstly, according to the localization accuracy requirement, this approach performs the motion paths segmentation in target area, and meanwhile merges the similar motion path segments based on the Mann-Whitney rank sum test. Then, a signal clustering algorithm based on the similar Received Signal Strength (RSS) sequence segments is adopted to guarantee the physical adjacency of the RSS samples in the same cluster. Finally, the backbone nodes based diffusion mapping is used to construct the mapping relations between the physical and signal spaces, and the motion user localization is consequently achieved. The experimental results indicate that compared with the existing WLAN indoor mapping and localization approaches, the proposed one is able to achieve higher mapping and localization accuracy without motion sensor assistance or location fingerprint database construction.
- Wireless Local Area Network (WLAN) /
- Indoor localization /
- Behavior analysis /
- Mann-Whitney rank sum test /
- Space mapping

HTML全文

图 1 系统架构

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图 2 目标区域结构图

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图 3 目标区域图像

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图 4 不同环境中的距离度量比较

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图 5 某一RSS序列均值滤波结果

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图 6 不同假设模式下的运动路径仿真结果

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图 7 运动路径片段聚类结果

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图 9 物理与信号逻辑图映射关系

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图 8 骨干节点集合重要性对比

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图 10 目标区域划分结果

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图 11 映射精度对比

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图 12 不同假设模式下的定位误差

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图 13 不同系统的定位误差

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图 14 不同物理相似度阈值下的定位误差

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