Wireless location estimation with the assistance of virtual base stations

Chien Huan Chen*, Kai-Ten Feng, Chao Lin Chen, Po Hsuan Tseng

*Corresponding author for this work

Research output: Contribution to journalArticle

18 Scopus citations


In recent years, wireless location estimation has attracted a significant amount of attention in different areas. Various types of radio signals are applied for the development of location-estimation algorithms. In this paper, the range measurements acquired from the received time-based information are adopted, and the modified least square (LS) method is utilized to process the raw data and to finally locate the target object. Practical issues, such as the nonline-of-sight (NLOS) errors and the geometric dilution of precision (GDOP) effect, are of concern. The NLOS error will cause a large nonnegative bias while measuring the propagation delay, which will lead to an unreliable result for location estimation. On the other hand, a large GDOP value corresponds to a poor geometric topology, which will result in inferior performance by adopting most of the existing location algorithms. The proposed location-estimation algorithms with virtual base stations (VBSs) will both mitigate the influence from the NLOS errors by imposing the geometric constraints and reduce the GDOP effect by incorporating the assisted VBSs. Two iterative schemes are proposed, including the center-of-gravity-based VBS (VBS-CG) and the minimal GDOP-based VBS (VBS-MG) algorithms, to determine the required number and the locations of the assisted VBSs. The proposed VBS algorithms are compared with other existing location-estimation schemes via simulations. The performance of the VBS-MG algorithm is observed to outperform the other schemes, particularly under the environments with larger NLOS errors and poor geometric layouts.

Original languageEnglish
Pages (from-to)93-106
Number of pages14
JournalIEEE Transactions on Vehicular Technology
Issue number1
StatePublished - 12 Feb 2009


  • Geometric dilution of precision (GDOP)
  • Nonline-of-sight (NLOS) errors
  • Time of arrival (TOA)
  • Two-step least square (LS) method
  • Wireless location estimation

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