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Removal of sensor tilt noise in fluxgate gradiometer survey data by applying one‐dimensional wavelet filtering
Author(s) -
Note Nicolas,
De Smedt Philippe,
Saey Timothy,
Gheyle Wouter,
Stichelbaut Birger,
Van den Berghe Hanne,
Bourgeois Jean,
Van Eetvelde Veerle,
Van Meirvenne Marc
Publication year - 2017
Publication title -
archaeological prospection
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.785
H-Index - 38
eISSN - 1099-0763
pISSN - 1075-2196
DOI - 10.1002/arp.1574
Subject(s) - gradiometer , noise (video) , wavelet , computer vision , artificial intelligence , computer science , magnetometer , fluxgate compass , noise reduction , smoothing , remote sensing , acoustics , geology , physics , magnetic field , image (mathematics) , quantum mechanics
Archaeological prospection with magnetometer instruments is performed in a wide range of field configurations, ranging from single probe setups to mobile arrays that allow combining multiple sensors. The latter type, whereby instruments are mounted onto a cart system, are particularly prone to motion‐induced noise. Sensor tilt, for example, causes in‐line noise that can obscure magnetic variations present. To remediate these effects, image processing techniques are the most frequently applied. However, while efficient in producing more levelled data plots, these procedures are often associated with a smoothing penalty whereby low‐intensity or small‐scale anomalies are masked. We propose a one‐dimensional signal processing approach, based on discrete wavelet analysis. By selecting wavelets that correspond to the motion‐induced noise patterns, such effects can be targeted more precisely, reducing the risk of feature masking or artefact creation. Evaluation of the proposed procedure on three fluxgate gradiometer datasets collected with a hand‐propelled push‐cart system, proved it a valid and more dedicated method to reduce the impact of motion induced noise in magnetometry data collected with cart mounted array setups.