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Accurate indoor positioning by combining sensor fusion and obstruction compensation
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-1858-9645
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-9471-8405
2023 (English)In: 2023 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Institute of Electrical and Electronics Engineers (IEEE), 2023Conference paper, Published paper (Refereed)
Abstract [en]

Our dependency on Global Navigation Satellite System (GNSS) for getting directions, tracking items, locating friends, or getting maps of the world has increased tremendously over the last decade. However, as soon as we enter a building, the signal strength of the satellites is too low, and we need to resort to other technologies to achieve the same goals. An Indoor Positioning System (IPS) may utilize a wide range of methods for positioning a device, such as fingerprinting, multilateration, or sensor fusion, while using one or several radio technologies to measure Received Signal Strength (RSS) or Time of Arrival(ToA). Sensor fusion is an efficient approach where an Inertial Measurement Unit (IMU) is combined with, e.g., RSS measurements converted to distances. But this approach has significant drawbacks in areas where, e.g., walls or large objects obstruct the signal path, which introduces bias in the distance estimates. This paper addresses the bias caused by signal path obstruction by compensating the measured RSS with localized RSS attenuation adjustments and thereby increasing the accuracy of the sensor fusion model significantly. We also show that a system can learn the compensation parameters over time, reducing the installationefforts and achieving higher accuracy than a fingerprinting-based system.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023.
Series
International Conference on Indoor Positioning and Indoor Navigation, ISSN 2162-7347, E-ISSN 2471-917X
Keywords [en]
IPS, RTLS, Indoor Positioning, Fingerprinting, Multilateration, Sensor Fusion
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mau:diva-62911DOI: 10.1109/IPIN57070.2023.10332536Scopus ID: 2-s2.0-85180781818ISBN: 979-8-3503-2011-4 (electronic)ISBN: 979-8-3503-2012-1 (print)OAI: oai:DiVA.org:mau-62911DiVA, id: diva2:1801945
Conference
IEEE 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), 25-28 September 2023, Nuremberg
Available from: 2023-10-03 Created: 2023-10-03 Last updated: 2024-02-05Bibliographically approved
In thesis
1. Scaling Indoor Positioning: improving accuracy and privacy of indoor positioning
Open this publication in new window or tab >>Scaling Indoor Positioning: improving accuracy and privacy of indoor positioning
2023 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Our phones have many uses for positioning technologies, such as navigation, LocationBased Services (LBS), emergency positioning, fitness applications, and advertising. We trust our phones and wearables to be location-aware. However, as soon as we enter a building, we can no longer use GPS signals, as their already weak signals are well below the background noise of the environment. This requires us to develop alternatives, such as installing active radio beacons, using existing radio infrastructure, applying environmental sensing based on barometric pressure and magnetic fields, or utilizing Inertial Measurement Units (IMUs) to estimate the user location. This licentiate thesis aims to evaluate beacon-based indoor positioning, where we assume installing a set of small battery-powered Bluetooth low-energy (BLE) beacons are possible. In particular, the thesis addresses essential factors such as installation effort, accuracy, the privacy aspects of an Indoor Positioning System(IPS), and mitigation of accuracy issues related to radio signal shadowing in complex indoor environments. The goal is to solve some obstacles to the widespread adoption of indoor positioning solutions.

Place, publisher, year, edition, pages
Malmö: Malmö University Press, 2023. p. 61
Series
Studies in Computer Science ; 24
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-62916 (URN)10.24834/isbn.9789178774234 (DOI)978-91-7877-422-7 (ISBN)978-91-7877-423-4 (ISBN)
Presentation
2023-11-07, F415, Orkanen, Nordenskiöldsg. 10, 15:00
Opponent
Supervisors
Available from: 2023-10-03 Created: 2023-10-03 Last updated: 2023-11-17Bibliographically approved

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Engström, JimmyPersson, Jan A.

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