A Framework for efficient cooperative localization with non-Gaussian ranging error distributions

Shenghong Li, Mark Hedley, Iain B. Collings

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Abstract

Cooperative localization takes advantage of the range measurements between neighbouring agents to improve both the availability and accuracy of positioning systems. Distributed belief propagation is a promising technique for data fusion in cooperative localization. Difficulties with belief propagation lie in reducing the required communication overhead and computational complexity. Most of the existing works on this subject are based on Gaussian ranging error models, which are fine for outdoor applications but not suitable for harsh propagation environments such as indoor and urban areas. In this paper, a framework for efficient cooperative localization is proposed, which can be applied to systems with non-Gaussian ranging error distributions. The communication and computational cost is reduced by passing approximate beliefs represented by Gaussian distributions between neighbours and by using an analytical approximation to compute peer-to-peer messages. The proposed scheme is validated experimentally on a deployed indoor localization system, and is shown to achieve high accuracy with low communication and computational cost.
Original languageEnglish
Title of host publicationIGNSS 2015
Subtitle of host publicationInternational Global Navigation Satellite Systems Society Symposium : conference papers
Place of PublicationGold Coast, QLD
PublisherInternational Global Navigation Satellite Systems Society (IGNSS)
Number of pages15
Publication statusPublished - 2015
EventInternational Global Navigation Satellite Systems Society Symposium (2015) - Gold Coast, QLD
Duration: 14 Jul 201516 Jul 2015

Conference

ConferenceInternational Global Navigation Satellite Systems Society Symposium (2015)
CityGold Coast, QLD
Period14/07/1516/07/15

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Keywords

  • cooperative localization
  • belief propagation
  • indoor positioning
  • ranging error distribution

Cite this

Li, S., Hedley, M., & Collings, I. B. (2015). A Framework for efficient cooperative localization with non-Gaussian ranging error distributions. In IGNSS 2015: International Global Navigation Satellite Systems Society Symposium : conference papers Gold Coast, QLD: International Global Navigation Satellite Systems Society (IGNSS).