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Position and orientation estimation of a permanent magnet using a small-scale sensor array
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0001-6630-243X
2018 (English)In: I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference: Discovering New Horizons in Instrumentation and Measurement, Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 1-5Conference paper, Published paper (Refereed)
Abstract [en]

A maximum likelihood estimator for the determination of the position and orientation of a permanent magnet using an array of magnetometers is presented. To reduce the complexity and increase the robustness of the estimator, the likelihood function is concentrated and an iterative solution method for the resulting low-dimensional optimization problem is presented. The performance of the estimator is experimentally evaluated with a miniaturized sensor array that consists of 32 magnetometer triads. The results are compared to the Cramér-Rao bound for the estimation problem at hand. The comparisons show that the performance of the estimator is close to the Cramer-Rao bound; hence, the estimator is close to optimal. Further, the results illustrate that even with a matchbox-sized array and a small magnet with a dipole moment that has a magnitude of 7 2 · 10-3 Am2 the position and orientation of the magnet can, within a 80×80×80 mm volume, be estimated with a root mean square error of less than 10 mm and 15 deg, respectively.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2018. p. 1-5
Keywords [en]
Cramer-Rao bounds, Iterative methods, Magnetometers, Mean square error, Permanent magnets, Estimation problem, Iterative solution methods, Likelihood functions, Low dimensional, Maximum likelihood estimator, Optimization problems, Position and orientations, Root mean square errors, Maximum likelihood estimation
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-238084DOI: 10.1109/I2MTC.2018.8409526Scopus ID: 2-s2.0-85050717343ISBN: 9781538622223 (print)OAI: oai:DiVA.org:kth-238084DiVA, id: diva2:1278007
Conference
2018 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2018, 14 May 2018 through 17 May 2018
Note

Conference code: 137883; Export Date: 30 October 2018; Conference Paper

QC 20190111

Available from: 2019-01-11 Created: 2019-01-11 Last updated: 2019-01-11Bibliographically approved

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Jaldén, Joakim

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  • apa
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