A Compressed Sensing Algorithm for Magnetic Dipole Localization

A Compressed Sensing Algorithm for Magnetic Dipole Localization

This paper proposes an algorithm to localize a magnetic dipole using a limited number of noisy measurements from magnetic field sensors. The algorithm is based on the theory of compressed sensing, and exploits the sparseness of the magnetic dipole in space. Beforehand, a basis consisting of magnetic...

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Bibliographic Details
Published in:IEEE sensors journal Vol. 22; no. 15; pp. 14825 - 14833
Main Authors: de Gijsel, Stefan L., Vijn, Aad R. P. J., Tan, Reinier G.
Format: Journal Article
Language:English
Published: New York IEEE 01-08-2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Compressed sensing
Dipole moments
Iterative methods
Localization
magnetic anomaly detection
Magnetic dipoles
Magnetic domains
Magnetic fields
Magnetic moments
Magnetic resonance imaging
Magnetic sensors
Magnetism
Optimization
Representations
sensor systems and applications
Sensors
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Summary:This paper proposes an algorithm to localize a magnetic dipole using a limited number of noisy measurements from magnetic field sensors. The algorithm is based on the theory of compressed sensing, and exploits the sparseness of the magnetic dipole in space. Beforehand, a basis consisting of magnetic dipole fields belonging to individual dipoles in an evenly spaced 3D grid within a specified search domain is constructed. In the algorithm, a number of sensors is chosen which measure all three magnetic field components. The sensors are chosen optimally using QR pivoting. Using the pre-constructed basis and the obtained field measurements, a sparse representation in the location domain is computed using <inline-formula> <tex-math notation="LaTeX">\ell _{{1}} </tex-math></inline-formula> optimization. Based on the resulting sparse representation, the location and magnetic moment of the magnetic dipole are estimated. An extension to an iterative method is implemented, where the basis and chosen sensors improve after every location estimate. Numerical simulations have been performed to verify the algorithm, and experiments have been done for validation. The proposed algorithm is shown to be effective in localizing magnetic dipoles.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2022.3184814