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On-The-Fly Geometric Calibration of Inertial Sensor Arrays
KTH, School of Electrical Engineering (EES), Information Science and Engineering.
KTH, School of Electrical Engineering (EES), Information Science and Engineering.ORCID iD: 0000-0002-3054-6413
KTH, School of Electrical Engineering (EES), Information Science and Engineering.ORCID iD: 0000-0001-6630-243X
2017 (English)In: 2017 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 2017Conference paper, Published paper (Refereed)
Abstract [en]

We present a maximum likelihood estimator for estimating the positions of accelerometers in an inertial sensor array. This method simultaneously estimates the positions of the accelerometers and the motion dynamics of the inertial sensor array and, therefore, does not require a predefined motion sequence nor any external equipment. Using an iterative block coordinate descent optimization strategy, the calibration problem can be solved with a complexity that is linear in the number of time samples. The proposed method is evaluated by Monte-Carlo simulations of an inertial sensor array built out of 32 inertial measurement units. The simulation results show that, if the array experiences sufficient dynamics, the position error is inversely proportional to the number of time samples used in the calibration sequence. Further, results show that for the considered array geometry and motion dynamics in the order of 2000 degrees/s and 2000 degrees/s(2), the positions of the accelerometers can be estimated with an accuracy in the order of 10(-6) m using only 1000 time samples. This enables fast on-the-fly calibration of the geometric errors in an inertial sensor array by simply twisting it by hand for a few seconds.

Place, publisher, year, edition, pages
2017.
Series
International Conference on Indoor Positioning and Indoor Navigation, ISSN 2162-7347
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-220651ISI: 000417415600018ISBN: 978-1-5090-6299-7 OAI: oai:DiVA.org:kth-220651DiVA, id: diva2:1172921
Conference
8th International Conference on Indoor Positioning and Indoor Navigation (IPIN), SEP 18-21, 2017, Sapporo, JAPAN
Note

QC 20180111

Available from: 2018-01-11 Created: 2018-01-11 Last updated: 2018-02-20Bibliographically approved

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Carlsson, HåkanSkog, IsaacJaldén, Joakim

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
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  • Other locale
More languages
Output format
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  • asciidoc
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