IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v76y2021i2d10.1007_s11235-020-00709-2.html
   My bibliography  Save this article

Research on a factor graph-based robust UWB positioning algorithm in NLOS environments

Author

Listed:
  • Xin Li

    (China University of Mining and Technology
    Mine Digitization Engineering Research Center of Ministry of Education of the People’s Republic of China)

  • Yang Wang

    (China University of Mining and Technology)

Abstract

In a non-line-of-sight (NLOS) environment, ultra-wide band (UWB) high accuracy positioning has been one of the hot topics in studying indoor positioning. In this paper, a factor graph-based UWB positioning algorithm has been proposed based on an improved Turkey robust kernel. It has overcome not only the defect of the least squares algorithm for UWB positioning against non-Gaussian noise but also eliminated the shortcoming of Turkey robust kernel against over-optimization. Aiming at the character of UWB data generally larger than its true value due to barriers, robust kernel will be added into merely big ranging data. However, due to the presence of small ranging data possibly caused by error positioning, the squares of residuals will be taken as the optimized objective function. The experimental result proves that UWB positioning algorithm based on the improved Turkey robust kernel outperforms ordinary UWB positioning algorithms in NLOS environments, with the average positioning accuracy improved by around 20–30%.

Suggested Citation

  • Xin Li & Yang Wang, 2021. "Research on a factor graph-based robust UWB positioning algorithm in NLOS environments," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 76(2), pages 207-217, February.
    • Handle: RePEc:spr:telsys:v:76:y:2021:i:2:d:10.1007_s11235-020-00709-2
    DOI: 10.1007/s11235-020-00709-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-020-00709-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-020-00709-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Narathep Phruksahiran, 2023. "Improvement of source localization via cellular network using machine learning approach," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(2), pages 291-299, February.

    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:spr:telsys:v:76:y:2021:i:2:d:10.1007_s11235-020-00709-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.