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基于Wi-Vi指纹的智能手机室内定位方法

黄刚 胡钊政 蔡浩 陶倩文 李祎承

黄刚, 胡钊政, 蔡浩, 陶倩文, 李祎承. 基于Wi-Vi指纹的智能手机室内定位方法. 自动化学报, 2020, 46(2): 320-331. doi: 10.16383/j.aas.2018.c170189
引用本文: 黄刚, 胡钊政, 蔡浩, 陶倩文, 李祎承. 基于Wi-Vi指纹的智能手机室内定位方法. 自动化学报, 2020, 46(2): 320-331. doi: 10.16383/j.aas.2018.c170189
HUANG Gang, HU Zhao-Zheng, CAI Hao, TAO Qian-Wen, LI Yi-Cheng. Smartphone-based Accurate Indoor Positioning From Wi-Vi Fingerprints. ACTA AUTOMATICA SINICA, 2020, 46(2): 320-331. doi: 10.16383/j.aas.2018.c170189
Citation: HUANG Gang, HU Zhao-Zheng, CAI Hao, TAO Qian-Wen, LI Yi-Cheng. Smartphone-based Accurate Indoor Positioning From Wi-Vi Fingerprints. ACTA AUTOMATICA SINICA, 2020, 46(2): 320-331. doi: 10.16383/j.aas.2018.c170189

基于Wi-Vi指纹的智能手机室内定位方法

doi: 10.16383/j.aas.2018.c170189
基金项目: 

国家自然科学基金 51679181

湖北省技术创新项目重大专项 2016AAA007

湖北省留学人员科技活动项目择优资助经费 2016- 12

详细信息
    作者简介:

    黄刚   武汉理工大学博士研究生.主要研究方向为计算机视觉和室内/室外定位. E-mail: gh@whut.edu.cn

    蔡浩   武汉理工大学博士研究生.主要研究方向为室内/室外定位.E-mail: caihao@whut.edu.cn

    陶倩文  武汉理工大学智能交通中心博士研究生.主要研究方向为三维计算机视觉, 室内定位与车辆定位. E-mail:tqw@whut.edu.cn

    李祎承   武汉理工大学博士研究生.主要研究方向为计算机视觉, 车载视觉定位. E-mail: ycli@whut.edu.cn

    通讯作者:

    胡钊政  武汉理工大学教授.主要研究方向为计算机视觉, 室内/室外定位和主动视觉监控系统.本文通信作者. E-mail: zzhu@whut.edu.cn

Smartphone-based Accurate Indoor Positioning From Wi-Vi Fingerprints

Funds: 

National Natural Science Foundation of China 51679181

the Major Project of Technological Innovation in Hubei Province 2016AAA007

the Science-technology Funds for Overseas Chinese Talents of Hubei Province 2016- 12

More Information
    Author Bio:

    HUANG Gang  Ph.D. candidate at Wuhan University of Technology. His research interest covers computer vision, indoor/outdoor localization

    CAI Hao    Ph.D. candidate at Wuhan University of Technology. His research interest covers indoor/outdoor localization

    TAO Qian-Wen    Ph.D. candidate at Wuhan University of Technology. Her research interest covers 3D computer vision, indoor localization, and vehicle localization

    LI Yi-Cheng    Ph.D. candidate at Wuhan University of Technology. His research interest covers computer vision, vision based vehicle localization

    Corresponding author: HU Zhao-Zheng   Professor at Wuhan University of Technology. His research interest covers computer vision, indoor/outdoor localization, active surveillance system. Corresponding author of this paper
  • 摘要: 室内定位是近些年国内外研究的热点, 但是目前的室内定位技术在适用性、稳定性和推广性方面仍然存在诸多问题.针对目前室内定位技术的不足, 面向公共室内场景的人员自定位问题, 本文创新性地提出以室内广泛存在、均匀分布的消防安全出口标志为路标(Landmark), 提出以Wi-Vi指纹-WiFi与视觉(Vision)信息相融合的指纹, 为位置表征的多尺度定位方法.该方法首先利用室内广泛存在的WiFi无线信号进行粗定位, 缩小定位范围; 然后在WiFi定位的基础上通过视觉全局和局部特征匹配实现图像级定位和验证; 最后参考消防安全出口标志的空间坐标精确计算用户的位置信息.实验中, 通过市面上流行的不同型号智能手机在12 000平米办公楼和4万平米商场分别进行实地定位测试.测试结果表明:该方法可以达到实时定位的要求, 图像级定位准确率均在97 %以上, 平均定位误差均在0.5米以下.本文所提出的基于Wi-Vi指纹智能手机定位方法为高精度室内定位问题建议了一种新的解决思路.
    Recommended by Associate Editor XU De
    1)  本文责任编委 徐德
  • 图  1  WiFi与视觉相融合的定位指纹— Wi-Vi指纹

    Fig.  1  WiFi and vision integrated positioning fingerprint — Wi-Vi fingerprint

    图  2  Wi-Vi指纹定位技术示意图

    Fig.  2  Procedures of Wi-Vi fingerprint based positioning method

    图  3  基于Wi-Vi指纹定位的Android软件使用示意图

    Fig.  3  Illustration of the Wi-Vi based Android application

    图  4  办公楼4、5楼CAD平面图(方块表示标志消防安全出口标志; 预先对每个出口标志进行编号)

    Fig.  4  CAD map of the fourth and fifth floor of office building (Exit signs are represented by blocks; Exit signs are pre-numbered)

    图  5  奥山世纪城3楼和−1楼CAD平面图(方块表示消防安全出口标志, −1楼标志过于密集, 仅用虚线标出出口标志集中区域; 预先对每个出口标志进行编号)

    Fig.  5  CAD map of the third floor and −1st floor of Orsun century city (Exit signs are represented by blocks, signs of −1st floor are not listed here due to too dense of signs; Exit signs are pre-numbered)

    图  6  实验中采集的WiFi数据分布和图像数据

    Fig.  6  Collected WiFi data distribution and image data

    图  7  WiFi定位结果

    Fig.  7  The result of WiFi positioning

    图  8  图像全局特征与局部特征匹配

    Fig.  8  Holistic and local feature matching for a pair of image

    图  9  图像级定位结果

    Fig.  9  The results of image-level positioning

    图  10  度量级定位修正后的最终定位结果

    Fig.  10  The results of final positioning after matric positioning

    表  1  Wi-Vi指纹

    Table  1  Wi-Vi fingerprint

    索引 Wi-Vi特征
    1 WiFi指纹 MAC [00238975abc0, 24dec63766a0, 24dec637ac40, 24dec638f120, 00238979acc0, 002389799c80, 24dec6379740, 24dec6390fe0, 24dec63905e0, 24dec6376f40, 002389798be0, 00238975b1b0]
    RSSI (dBm) [-81, -81, -83, -81, -63, -81, -82, -73, -78, -83, -86, -85]
    图像数据 全局特征 [211, 80, 47, 62, 40, 234, 93, 24, 180, 91, 195, 245, 215, 156, 59, 121, 196, 129, 255, 199, 175, 5, 119, 117, 209, 35, 120, 129, 124, 85, 190, 83]
    局部特征 (416, 306), [157, 73, 7, 244, 149, 70, 239, 252, 148, 226, 66, 66, 113, 99, 49, 227, 88, 100, 50, 239, 105, 212, 61, 174, 41, 139, 239, 4, 63, 121, 48, 160] ……
    单应矩阵 [1.1, 3.2, 336.0; 0, 3.5, 281.0; 0, 0, 1]
    参考坐标(mm) (8 000, 7 800, 2 200); (8 000, 8 050, 2 200); (8 000, 8 050, 1 050); (8 000, 7 800, 1 050)
    下载: 导出CSV

    表  2  定位误差与定位耗时对比实验

    Table  2  Positioning error results and time consuming comparison

    方法 平均定位耗时(s) 平均定位误差(m) 误差$ \leq 1 $ m的占比(%)
    本文提出的方法 0.6 0.3 98
    文献[13]的方法 0.1 4.5 30
    文献[14]的方法 5.0 3.1 31
    文献[18]的方法 1.8 0.8 77
    文献[19]的方法 15.1 1.0 94
    文献[22]的方法 22 3.1 37
    文献[23]的方法 2.5 2.0 35
    下载: 导出CSV
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  • 收稿日期:  2017-04-10
  • 录用日期:  2018-01-14
  • 刊出日期:  2020-03-06

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