Factor graph based simultaneous localization and mapping using multipath channel information

Erik Leitinger, Florian Meyer, Fredrik Tufvesson, Klaus Witrisal

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Radio-based localization has the potential to provide centimeter-level position information. In this paper we apply joint probabilistic data association to multipath-assisted simultaneous localization and mapping (SLAM) for this purpose. In multipath-assisted localization, position-related information in multipath components (MPCs) is exploited to increase the accuracy and robustness of indoor tracking. Based on a recently introduced loopy belief propagation multipath-assisted localization scheme that performs probabilistic data association jointly with agent state estimation, we build a method for SLAM without using apriori known environment maps. The proposed method is highly accurate and robust in localizing a mobile agent while building up an environment feature map. It scales well in all relevant systems parameters and has a very low computational complexity.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017
PublisherInstitute of Electrical and Electronics Engineers
Pages652-658
Number of pages7
ISBN (Electronic)9781509015252
DOIs
Publication statusPublished - 29 Jun 2017
Event2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017 - Paris, France
Duration: 21 May 201725 May 2017

Conference

Conference2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017
Country/TerritoryFrance
CityParis
Period21/05/1725/05/17

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture

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