Metal detector depth estimation algorithms

Jay Marble; Ian McMichael

doi:10.1117/12.817868

4 May 2009 Metal detector depth estimation algorithms

Jay Marble, Ian McMichael

Proceedings Volume 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV; 73030L (2009) https://doi.org/10.1117/12.817868
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

This paper looks at depth estimation techniques using electromagnetic induction (EMI) metal detectors. Four algorithms are considered. The first utilizes a vertical gradient sensor configuration. The second is a dual frequency approach. The third makes use of dipole and quadrapole receiver configurations. The fourth looks at coils of different sizes. Each algorithm is described along with its associated sensor. Two figures of merit ultimately define algorithm/sensor performance. The first is the depth of penetration obtainable. (That is, the maximum detection depth obtainable.) This describes the performance of the method to achieve detection of deep targets. The second is the achievable statistical depth resolution. This resolution describes the precision with which depth can be estimated. In this paper depth of penetration and statistical depth resolution are qualitatively determined for each sensor/algorithm. A scientific method is used to make these assessments. A field test was conducted using 2 lanes with emplaced UXO. The first lane contains 155 shells at increasing depths from 0" to 48". The second is more realistic containing objects of varying size. The first lane is used for algorithm training purposes, while the second is used for testing. The metal detectors used in this study are the: Geonics EM61, Geophex GEM5, Minelab STMR II, and the Vallon VMV16.

Citation Download Citation

Jay Marble and Ian McMichael "Metal detector depth estimation algorithms", Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73030L (4 May 2009); https://doi.org/10.1117/12.817868

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