A Smartphone-Based Indoor Positioning System Using Fuzzy Theory and WLAN Mapping Algorithm

被引:0
|
作者
Li, Chao [1 ]
Jiang, Zhuqing [1 ]
Huang, Chengkai [1 ]
Liu, Xinmeng [1 ]
Yang, Yuying [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China
关键词
Smartphone-Based Indoor Positioning System; Fuzzy Theory; Fuzzy Step Length Detection; WLAN Mapping Algorithm;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As we all know, the accuracy of GPS become worse indoors due to the satellite signal attenuation. However, people spend most of his or her time in the indoor environment and the location-based service is needed in the indoor environment. Hence, many indoor positioning techniques have been researched to provide location-based service for visitors in public buildings such as museums, galleries, etc. However, the distinguish of human's moving patterns and initial position detection are two difficult problems in Pedestrian Dead Reckoning (PDR) system. Therefore, A smartphone-based indoor positioning system (called Improved Pedestrian Dead Reckoning, IPDR) using fuzzy theory and WLAN mapping algorithm is presented to solve these problems. In our proposed system, we propose a method called fuzzy step length detection which can distinguish five different human's moving patterns and handle various ways of holding the phone. The WI:AN mapping algorithm could calculate the initial position. Calibrated position can be obtained from the IPDR position and the mapping position from WLAN map acquired in advance. The performance of our IPDR system is verified via a set of simulations and the result is positive.
引用
收藏
页码:2177 / 2181
页数:5
相关论文
共 50 条
  • [31] An Indoor Positioning Algorithm Based on Received Signal Strength of WLAN
    Pei, Chuanjie
    Cai, Yanhong
    Ma, Zhengxin
    PROCEEDINGS OF THE 2009 PACIFIC-ASIA CONFERENCE ON CIRCUITS, COMMUNICATIONS AND SYSTEM, 2009, : 516 - 519
  • [32] WLAN indoor positioning based on SALDE-SVM algorithm
    Xu X.-S.
    Wu X.-F.
    Zhang T.
    Yan L.-Y.
    Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology, 2017, 25 (06): : 731 - 737
  • [33] Smartphone-Based Pedestrian Dead Reckoning for 3D Indoor Positioning
    Geng, Jijun
    Xia, Linyuan
    Xia, Jingchao
    Li, Qianxia
    Zhu, Hongyu
    Cai, Yuezhen
    SENSORS, 2021, 21 (24)
  • [34] Smartphone-based hybrid indoor positioning system with integration of Wi-Fi fingerprinting and magnetic matching
    Huang, Pei-Yu
    Jan, Shau-Shiun
    De Lorenzo, David S.
    Tseng, Ivy
    PROCEEDINGS OF THE 29TH INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS+ 2016), 2016, : 1814 - 1823
  • [35] Magnetic Disturbance Detection for Smartphone-Based Indoor Positioning Systems With Unsupervised Learning
    Dong, Yinhuan
    Arslan, Tughrul
    Yang, Yunjie
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [36] Smartphone-based Accurate Indoor Positioning From Wi-Vi Fingerprints
    Huang G.
    Hu Z.-Z.
    Cai H.
    Tao Q.-W.
    Li Y.-C.
    Zidonghua Xuebao/Acta Automatica Sinica, 2020, 46 (02): : 320 - 331
  • [37] Smartphone Indoor Positioning System Based on Geomagnetic Field
    Cao, Limeng
    Kang, Ruiqing
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 1826 - 1830
  • [38] An Indoor Positioning System based on Inertial Sensors in Smartphone
    Sun, Yi
    Zhao, Yubin
    Schiller, Jochen
    2015 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2015, : 2221 - 2226
  • [39] A VLC Smartphone Camera Based Indoor Positioning System
    Li, Yiwei
    Ghassemlooy, Zabih
    Tang, Xuan
    Lin, Bangjiang
    Zhang, Yi
    IEEE PHOTONICS TECHNOLOGY LETTERS, 2018, 30 (13) : 1171 - 1174