Modeling Magnetic Fields using Gaussian Processes
2013 (English)In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013, IEEE conference proceedings, 2013, 3522-3526 p.Conference paper (Refereed)
Starting from the electromagnetic theory, we derive a Bayesian nonparametric model allowing for joint estimation of the magnetic field and the magnetic sources in complex environments. The model is a Gaussian process which exploits the divergence- and curl-free properties of the magnetic field by combining well-known model components in a novel manner. The model is estimated using magnetometer measurements and spatial information implicitly provided by the sensor. The model and the associated estimator are validated on both simulated and real world experimental data producing Bayesian nonparametric maps of magnetized objects.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2013. 3522-3526 p.
, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013, ISSN 1520-6149
IdentifiersURN: urn:nbn:se:liu:diva-88966DOI: 10.1109/ICASSP.2013.6638313ISI: 000329611503136ISBN: 978-1-4799-0356-6OAI: oai:DiVA.org:liu-88966DiVA: diva2:606538
2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 26-31, Vancouver, Canada
FunderSwedish Foundation for Strategic Research EU, FP7, Seventh Framework Programme