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Indoor Positioning Using Multi-Frequency RSS with Foot-Mounted INS
Swedish Defence Research Agency (FOI), Linköping, Sweden.
Swedish Defence Research Agency (FOI), Linköping, Sweden; KTH Royal Institute of Technology, Stockholm, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Swedish Defence Research Agency (FOI), Linköping, Sweden.ORCID iD: 0000-0002-1971-4295
2014 (English)In: Fifth International Conference on Indoor Positioning and Indoor Navigation, Institute of Electrical and Electronics Engineers (IEEE), 2014Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a system which combines a zero-velocity-update-(ZUPT-)aided inertial navigation system (INS), using a foot-mounted inertial measurement unit (IMU), with opportunistic use of multi-frequency received signal strength (RSS) measurements. The system does not rely on maps or pre-collected data from surveys of the radio-frequency (RF) environment. Instead it builds its own database of collected RSS measurements during the course of the operation. New RSS measurements are continuously compared with the stored values in the database, and when the user returns to a previously visited area this can thus be detected. This enables loop-closures to be detected online and used for error drift correction. The system utilises a distributed particle simultaneous localization and mapping (DP-SLAM) algorithm which provides a flexible 2D navigation platform that can be extended with more sensors. The experimental results presented in this paper indicates that the developed RSS SLAM algorithm can, in many cases, significantly improve the positioning performance of a foot-mounted INS. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2014.
Keyword [en]
RSS, SLAM, ZUPT, IMU, INS, Gaussian Processes, Particle Filter, Radial Basis Function
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-111802DOI: 10.1109/IPIN.2014.7275482ISBN: 978-146738054-6 (print)OAI: oai:DiVA.org:liu-111802DiVA: diva2:760560
Conference
Fifth International Conference on Indoor Positioning and Indoor Navigation (IPIN2014), 27–30 October 2014, Busan, Korea
Funder
Security Link
Available from: 2014-11-04 Created: 2014-11-04 Last updated: 2016-06-10Bibliographically approved

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Skoglund, Martin A.Hendeby, Gustaf

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Citation style
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  • vancouver
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Output format
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