IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v11y2015i8p753191.html
   My bibliography  Save this article

A Fuzzy Similarity Elimination Algorithm for Indoor Fingerprint Positioning

Author

Listed:
  • Yongle Chen
  • Wei Liu
  • Yongping Xiong
  • Jing Duan
  • Zhi Li
  • Hongsong Zhu

Abstract

Fingerprint positioning can take advantage of existing WLAN to achieve indoor locations, which has been widely studied. We analyzed the corresponding positions distribution of similar fingerprints, and then found that the fuzzy similarity between fingerprints is the root cause of the larger errors existing. According to clusters distribution feature of corresponding positions of the similar fingerprints, we proposed a K -Means+ clustering algorithm to achieve fine-grained fingerprint positioning. Due to the K -Means+ algorithm failing to locate the positions of outliers, we also designed a linear sequence matching algorithm to improve the outliers positioning, and reduce the impact of fuzzy similarity. Experimental results illustrate that our algorithm can get a maximum positioning error less than 5 m, which outperforms other algorithms. Meanwhile, all the positioning errors over 4 m in our algorithm are less than 2%. The positioning accuracy has been improved significantly.

Suggested Citation

  • Yongle Chen & Wei Liu & Yongping Xiong & Jing Duan & Zhi Li & Hongsong Zhu, 2015. "A Fuzzy Similarity Elimination Algorithm for Indoor Fingerprint Positioning," International Journal of Distributed Sensor Networks, , vol. 11(8), pages 753191-7531, August.
    • Handle: RePEc:sae:intdis:v:11:y:2015:i:8:p:753191
    DOI: 10.1155/2015/753191
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1155/2015/753191
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2015/753191?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:11:y:2015:i:8:p:753191. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.