Title
A Compressed Sensing Algorithm for Magnetic Dipole Localization
Author
de Gijsel, S.L.
Vijn, A.R.P.J.
Tan, R.G.
Publication year
2022
Abstract
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 ℓ1 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.
Subject
Compressed sensing
magnetic sensors
sensor systems and applications
Anomaly detection
Compressed sensing
Iterative methods
Location
Magnetic fields
Magnetic moments
Magnetometers
Compressed-Sensing
Dipole localization
Magnetic anomaly detection
Magnetic fields sensors
Noisy measurements
Optimisations
Sensing algorithms
Sensor systems and applications
Sparse representation
Magnetic resonance imaging
To reference this document use:
http://resolver.tudelft.nl/uuid:34341a89-9b82-4d9b-8b0a-cfb983216898
TNO identifier
980694
Publisher
Institute of Electrical and Electronics Engineers Inc.
ISSN
1530-437X
Source
IEEE Sensors Journal, 22 (22), 14825-14833
Document type
article