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Abstract Magnetometers are essential instruments in space physics, but their measurements are often contaminated by various external interference sources. In this work, we present a comprehensive review of existing magnetometer interference removal methods and introduce MAGPRIME (MAGnetic signal PRocessing, Interference Mitigation, and Enhancement), an open‐source Python library featuring a collection of state‐of‐the‐art interference removal algorithms. MAGPRIME streamlines the process of interference removal in magnetic field data by providing researchers with an integrated, easy‐to‐use platform. We detail the design, structure, and functionality of the library, as well as its potential to facilitate future research by enabling rapid testing and customization of interference removal methods. Using the MAGPRIME Library, we present two Monte Carlo benchmark results to compare the efficacy of interference removal algorithms in different magnetometer configurations. In Benchmark A, the Underdetermined Blind Source Separation (UBSS) and traditional gradiometry algorithms surpass the uncleaned boom‐mounted magnetometers, achieving improved correlation and reducing median error in each simulation. Benchmark B tests the efficacy of the suite of MAGPRIME algorithms in a boomless magnetometer configuration. In this configuration, the UBSS algorithm proves to significantly reduce median error, along with improvements in median correlation and signal to noise ratio. This study highlights MAGPRIME's potential in enhancing magnetic field measurement accuracy in various spacecraft designs, from traditional gradiometry setups to compact, cost‐effective alternatives like bus‐mounted CubeSat magnetometers, thus establishing it as a valuable tool for researchers and engineers in space exploration and magnetism studies.
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This content will become publicly available on March 5, 2026
Enabling Small Anomaly Detection using Finite-Difference Magnetic Gradiometry
Magnetometry is used to detect ferrous objects at various scales, but detecting small-size, compact sources that produce small-amplitude anomalies in the shallow subsurface remains challenging. Magnetic anomalies are often approximated as dipoles or volumes of dipoles that can be located, and their source parameters (burial depth, magnetization direction, magnetic susceptibility, etc.) are characterized using scalar or vector magnetometers. Both types of magnetometers are affected by space weather and cultural noise sources that map temporal variations into spatial variations across a survey area. Vector magnetometers provide more information about detected bodies at the cost of extreme sensitivity to orientation, which cannot be reliably measured in the field. Magnetic gradiometry addresses the problem of temporal-to-spatial mapping and reduces distant noise sources, but the heading error challenges remain, motivating the need for magnetic gradient tensor (MGT) invariants that are relatively insensitive to rotation. Here, we show that the finite size of magnetic gradiometers compared to the lengthscales of magnetic anomalies due to small buried objects affects the properties of the gradient tensor, including its symmetry and invariants. This renders traditional assumptions of magnetic gradiometry largely inappropriate for detecting and characterizing small-size anomalies. We then show how the properties of the finite-difference MGT and its invariants can be leveraged to map these small sources in the shallow critical zone, such as unexploded ordnance (UXO), landmines, and explosive remnants of war (ERW), using both synthetic and field data obtained with a triaxial magnetic gradiometer (TetraMag).
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- Award ID(s):
- 2044611
- PAR ID:
- 10586368
- Publisher / Repository:
- Society of Exploration Geophysicists
- Date Published:
- Journal Name:
- Geophysics
- Volume:
- 90
- Issue:
- 4
- ISSN:
- 1942-2156
- Page Range / eLocation ID:
- 1-63
- Subject(s) / Keyword(s):
- finite difference gradiometry magnetics magnetic tensor magnetometer
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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