Towards Automated Target Picking in Scalar Magnetic Unexploded Ordnance Surveys: An Unsupervised Machine Learning Approach for Defining Inversion Priors
Author:
Affiliation:
1. Crustal Magnetism Technology and Research Group, DTU Space, Technical University of Denmark, Centrifugevej Building 356, 2800 Kongens Lyngby, Denmark
2. UMag Solutions, Nørgaardsvej 26, 2800 Kongens Lyngby, Denmark
Abstract
Funder
Technical University of Denmark Discovery Grant
Publisher
MDPI AG
Subject
General Earth and Planetary Sciences
Link
https://www.mdpi.com/2072-4292/16/3/507/pdf
Reference15 articles.
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2. Detection of unexploded ordnance (UXO) using marine magnetic gradiometer data;Salem;Explor. Geophys.,2005
3. Interpretation of high-resolution low-altitude helicopter magnetometer surveys over sites contaminated with unexploded ordnance;Billings;J. Appl. Geophys.,2010
4. Zheng, Y., Li, S., Xing, K., and Zhang, X. (2021). Unmanned aerial vehicles for magnetic surveys: A review on platform selection and interference suppression. Drones, 5.
5. Kolster, M.E., Wigh, M.D., da Silva, E.L.S., Vilhelmsen, T.B., and Døssing, A. (2022). High-Speed Magnetic Surveying for Unexploded Ordnance Using UAV Systems. Remote Sens., 14.
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