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NLOS identification in range-based source localization: statistical approach

Abolfathi Momtaz, A ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1109/JSEN.2018.2810257
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2018
  4. Abstract:
  5. Least squares estimation is a widely-used technique for range-based source localization, which obtains the most probable position of mobile station. These methods cannot provide desirable accuracy in the case with a non line of sight (NLOS) path between mobile station and base stations. To circumvent this drawback, many algorithms have been proposed to identify and mitigate this error; however, they have a large run-time overhead. On the other hand, new positioning systems utilize a large set of base stations, and a practical algorithm should be fast enough to deal with them. In this paper, we propose a novel algorithm based on subspace method to identify and eliminate the NLOS error. Simulation studies show that our algorithm is faster and more accurate compared with other conventional methods, especially in the large-scale cases. © 2001-2012 IEEE
  6. Keywords:
  7. Non line of sight (NLOS) identification ; Subspace method ; Base stations ; Correlation methods ; Mathematical models ; Nonlinear optics ; Sensors ; Sorting ; Conventional methods ; Least squares estimation ; NLOS identifications ; Nonline of sight ; Source localization ; Statistical approach ; Sub-space methods ; Time of arrival (TOA) ; Eigenvalues and eigenfunctions
  8. Source: IEEE Sensors Journal ; Volume 18, Issue 9 , 1 May , 2018 , Pages 3745-3751 ; 1530437X (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/8304620