Paper
7 May 2007 Soil compensation techniques for the detection of buried metallic objects using electromagnetic sensors
Leonard R. Pasion, Douglas W. Oldenburg, Stephen D. Billings, David Sinex
Author Affiliations +
Abstract
Magnetic soils are a major source of false positives when searching for landmines or unexploded ordnance (UXO) with electromagnetic induction sensors. In adverse areas up to 30% of identified electromagnetic (EM) anomalies are attributed to geology. The main source of the electromagnetic response is the magnetic viscosity of the ferrimagnetic minerals magnetite and maghaemite. The EM phenomena that give rise to the response of magnetically viscous soil and metal are fundamentally different. The viscosity effects of magnetic soil can be accurately modelled by assuming a ferrite relaxation with a log-uniform distribution of time constants. The EM response of a metallic target is due to eddy currents induced in the target and is a function of the target's size, shape, conductivity and magnetic susceptibility. In this presentation, we consider different soil compensation techniques for time domain and frequency domain EM data. For both types of data we exploit the EM characteristics of viscous remnantly magnetized soil. These techniques will be demonstrated with time domain and frequency domain data collected on Kaho'olawe Island, Hawaii. A frequency domain technique based on modeling a negative log-linear in-phase and constant quadrature component was found to be very effective at suppressing false-alarms due to magnetic soils.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Leonard R. Pasion, Douglas W. Oldenburg, Stephen D. Billings, and David Sinex "Soil compensation techniques for the detection of buried metallic objects using electromagnetic sensors", Proc. SPIE 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII, 655326 (7 May 2007); https://doi.org/10.1117/12.728483
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Cited by 6 scholarly publications.
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KEYWORDS
Data modeling

Magnetism

Sensors

Electromagnetism

Polarization

Soil science

Geology

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