A survey on fusion-based indoor positioning

Xiansheng Guo, Nirwan Ansari, Fangzi Hu, Yuan Shao, Nkrow Raphael Elikplim, Lin Li

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Demands for indoor positioning based services (IPS) in commercial and military fields have spurred many positioning systems and techniques. Complex electromagnetic environments (CEEs) may, however, degenerate the accuracy and robustness of some existing single systems and techniques. To overcome this drawback, fusion-based positioning of multiple systems and/or techniques have been proposed to revamp the positioning performance in CEEs. In this paper, we survey the fusion-based indoor positioning techniques and systems from seminal works to elicit the state of the art within our proposed unified fusion-based positioning framework, which consists of three fusion characteristics: source, algorithm, and weight spaces. Different from other surveys, this survey summarizes and analyzes the existing fusion-based positioning systems and techniques from three characteristics. Meanwhile, discussions in terms of lessons, challenges, and countermeasures are also presented. This survey is invaluable for researchers to acquire a clear concept of indoor fusion-based positioning systems and techniques and also to gain insights from this survey to further develop other advanced fusion-based positioning systems and techniques in the future.

Original languageEnglish (US)
Article number8889728
Pages (from-to)566-594
Number of pages29
JournalIEEE Communications Surveys and Tutorials
Volume22
Issue number1
DOIs
StatePublished - Jan 1 2020

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Keywords

  • Indoor positioning based services (IPS)
  • complex electromagnetic environments (CEEs)
  • ensemble learning
  • fusion-based positioning

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