Anchor Selection for Localization in Large Indoor Venues

Omotayo Oshiga, Xiaowen CHU, Yiu Wing LEUNG, Joseph K Y NG

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

4 Citations (Scopus)


Many indoor localization systems rely on a set of reference anchors with known positions. A target's location is estimated from a set of distances between the target and its surrounding anchors, and hence the selection of anchors affects the localization accuracy. However, it remains a challenge to select the best set of anchors. In this paper, we study how to appropriately make use of the surrounding anchors for localizing a target. We first construct different candidate anchor clusters by selecting different number of anchors with the strongest received signals. Then for each candidate cluster, we propose a weighted min-max algorithm to provide a location estimation. Finally, we introduce a weighted geometric dilution of precision (w-GDOP) algorithm that combines the estimations from multiple clusters by quantifying their estimation accuracy. We evaluate the performance of our solution through simulations and real-world experiments. Our results show that the proposed anchor selection scheme and localization algorithm significantly improve the localization accuracy in large indoor environments.

Original languageEnglish
Title of host publication2018 IEEE/ACM 26th International Symposium on Quality of Service, IWQoS 2018
ISBN (Electronic)9781538625422
Publication statusPublished - 22 Jan 2019
Event26th IEEE/ACM International Symposium on Quality of Service, IWQoS 2018 - Banff, Canada
Duration: 4 Jun 20186 Jun 2018


Conference26th IEEE/ACM International Symposium on Quality of Service, IWQoS 2018

Scopus Subject Areas

  • Safety, Risk, Reliability and Quality
  • Management of Technology and Innovation
  • Computer Networks and Communications
  • Media Technology


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