Electromagnetic induction spectroscopy for clearing landmines

Won, I. J.; Keiswetter, Dean; Bell, Thomas H.

doi:10.1109/36.917876

Cited by 116 publications

(83 citation statements)

References 10 publications

(8 reference statements)

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“…The broadband response from time-domain EM induction instruments such as the Geonics EM-63 contains information about the shape and composition of buried metallic objects (i.e., targets) that is difficult to obtain with frequency-domain instruments operating at one frequency [1]. Similar information is also available from wideband frequency-domain instruments such as the Geophex GEM-3 [2,3]. In recent years, algorithms have been developed to estimate the location, shape, and composition (ferrous or non-ferrous metal) of targets using data from these broadband systems [4,5].…”

Section: Introductionmentioning

confidence: 90%

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Combining Advances in Em Induction Instrumentation and Inversion Schemes for Uxo Characterization

Oden¹

2012

PIER B

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Abstract-Several experimental time-domain EM induction instruments have recently been developed for unexploded ordnance (UXO) detection and characterization that use multiple transmitting and receiving coil combinations. One such system, the US Geological Survey's ALLTEM system, is unique in that it measures both the electrodynamic response (i.e., induced eddy currents) and the magneto-static response (i.e., induced magnetization). This allows target characterization based on the dyadic polarizability of both responses. This paper examines the numerical response of the ALLTEM instrument due to spheroidal, conductive, and permeable UXO targets; and to conductive and optionally viscous magnetic earth. An inversion scheme is presented for spheroidal targets that incorporates fully polarimetric measurements for both magneto-static and electro-dynamic excitations. The performance of the inversion algorithm is evaluated using both simulated and surveyed data. The results are examined as a function of the number of coil combinations, number of instrument locations, and uncertainty in sensor location and orientation. Results from the specific cases tested (prolate spheroids lying horizontally) show that 1) that collecting data from more than 12 sensor locations or from more than four coil combinations reduced the chances that inversion solutions would be from a local minimum, and 2) that uncertainties in position greater than 3 cm or in orientation greater than 10 degrees cause errors in the estimated spheroid principal lengths of greater than 100%. Soil conductivities less than 1 S/m contribute negligible interference to the target response, but viscous magnetic soils with permeabilities greater than 10 −6 MKS units do cause detrimental interference.

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Section: Introductionmentioning

confidence: 90%

“…First, the magnetic field below the surface is calculated at the center of the target using (2). Here the dyadic Green's function is now for the fields below the surface due to a dipole moment above the surface (see Appendix A),…”

Section: Alltem Modelingmentioning

confidence: 99%

Combining Advances in Em Induction Instrumentation and Inversion Schemes for Uxo Characterization

Oden¹

2012

PIER B

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“…Sweeping, detecting, and clearing landmines is possible thanks to electromagnetic induction spectroscopy. 4 There are some studies relating to a landmine detector assembled on a remote-controlled mobile platform or vehicle. 5 There are also landmine detectors with inductive and capacitive 6 RF microcontrollers, as well ones which are GPS-based, 7 and GPR-designed.…”

Section: Introductionmentioning

confidence: 99%

Motion planning for a landmine-detection robot

Shiao

et al. 2011

Artif Life Robotics

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“…17 Of course, as all real life objects has both magnetic and conducting properties and as these depends on the frequency due to many parameters, this will result in different spectra for different items, not only depending on the item itself (material, size and shape) but also on mutual orientation and position (distance, depth) and surrounding environment. It has been suggested, 20 that identification of mines and other items could be possible from EMIS spectra. This seems possible for different mines measured in free air, but when small mines are measured in soil, and background signals and clutter contributes to the spectra, identification turns out to be very difficult or even impossible.…”

Section: The Gpr and Emis Data Setsmentioning

confidence: 99%

A comparative and combined study of EMIS and GPR detectors by the use of independent component analysis

et al. 2005

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Independent Component Analysis (ICA) is applied to classify unexploded ordnance (UXO) on laboratory UXO test-field data, acquired by stand-off detection. The data are acquired by an Electromagnetic Induction Spectroscopy (EMIS) metal detector and a ground penetrating radar (GPR) detector. The metal detector is a GEM-3, which is a monostatic sensor measuring the response of the environment on a multi-frequency constant wave excitation field (300 Hz to 25 kHz), and the GPR detector is a stepped-frequency GPR with a monostatic bow-tie antenna (500 MHz to 2.5 GHz). For both sensors the in-phase and the quadrature responses are measured at each frequency. The test field is a box of soil where a wide range of UXOs are placed at selected positions. The position and movement of both of the detectors are controlled by a 2D-scanner. Thus the data are acquired at well-defined measurement points. The data are processed by the use of statistical signal processing based on ICA. An unsupervised method based on ICA to detect, discriminate, and classify the UXOs from clutter is suggested. The approach is studied on GPR and EMIS data, separately and compared. The potential is an improved ability: to detect the UXOs, to evaluate the related characteristics, and to reduce the number of false alarms from harmless objects and clutter.

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Electromagnetic induction spectroscopy for clearing landmines

Cited by 116 publications

References 10 publications

Combining Advances in Em Induction Instrumentation and Inversion Schemes for Uxo Characterization

Combining Advances in Em Induction Instrumentation and Inversion Schemes for Uxo Characterization

Motion planning for a landmine-detection robot

A comparative and combined study of EMIS and GPR detectors by the use of independent component analysis

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