Benjamin E. Barrowes

Broadband analytical magnetoquasistatic electromagnetic induction solution for a conducting and permeable spheroid

We use a hybrid model including asymptotic expressions of the spheroidal wave functions (SWFs) to obtain a reliable broadband solution for the electromagnetic induction (EMI) response from a conducting and permeable spheroid. We obtain this broadband response, valid in the magnetoquasistatic regime from zero to hundreds of kilohertz, by combining three different techniques, each applicable over a different frequency range. At low frequencies, the exact analytical solution is used. At midrange frequencies, asymptotic expressions for the angular and radial SWFs are incorporated into the exact solution in order to maintain a stable solution for the induced magnetic field. At higher frequencies, a small penetration approximation (SPA) solution is used when the SPA solution approaches the asymptotically assisted solution to within some predefined tolerance. Validation of this combined technique is accomplished through the comparison of the induced magnetic field predicted by our model to both a finite element/boundary integral (FE-BI) numerical solution and experimental data from various spheroids taken by an ultrawideband EMI instrument.

Simultaneous Identification of Multiple Unexploded Ordnance Using Electromagnetic Induction Sensors

The simultaneous detection and identification of multiple targets using electromagnetic induction (EMI) time-domain sensors remains a challenge due to the fast decay of the magnetic field with sensor-target distance. For example, the signal from a weak yet shallow target or clutter item can overshadow that from a much larger yet deeper unexploded ordnance (UXO), potentially resulting in erroneous localization and/or identification. We propose, in this paper, a method based on the Gauss-Newton algorithm for the inversion of multiple targets within the field of view of sensors operating at EMI frequencies (tens of hertz to a few hundred kilohertz). In order to minimize the number of unknowns to invert for, the polarizability tensor is written as a time-independent orientation matrix multiplied by a time-dependent diagonal intrinsic polarizability tensor. Similarly, position is supposed to be time independent so that both position and orientation angles are inverted only once using all time channels collected by the instrument. Moreover, using the dipole approximation, we are able to compute the Jacobian in closed form for instruments with either square or circular primary field coils, thus contributing to the speed of the algorithm. Validating results are shown based on the measurement data collected with two EMI sensors on various types of UXO.

A Man-Portable Vector Sensor for Identification of Unexploded Ordnance

The identification and discrimination of unexploded ordnance using low-frequency electromagnetic induction is an expensive and difficult process, typically beset by low data diversity and high positioning uncertainty. In this paper, we present the Man-Portable Vector (MPV) sensor, a new time-domain instrument designed to remedy these shortcomings by measuring all three vector components of the secondary magnetic field at five distinct points around each transmitter location. The MPV also has a laser positioning system that can give its location with millimeter precision. After describing the instrument in detail, we study its performance in various sets of measurements, using the tensor dipole model to analyze the data. We find that the sensor can detect deeply buried targets and identify some standard ordnance items. It can also resolve separate targets in cases where two objects share the field of view and produce overlapping signals. A new incarnation of the MPV, the MPV-II, is in an advanced stage of development.

Electromagnetic Induction From Highly Permeable and Conductive Ellipsoids Under Arbitrary Excitation: Application to the Detection of Unexploded Ordnances

The secondary field produced by 3-D highly permeable and conductive objects is computed in the electromagnetic induction regime, with the purpose of modeling unexploded ordnances (UXOs) and surrounding clutter. The analytical formulation is based on the ellipsoidal coordinate system that is able to model real 3-D geometries as opposed to bodies of revolutions like within a spheroidal approach. At the frequencies of interest (tens of hertz to hundreds of kilohertz), conduction currents in the soil are negligible, and the fields are computed in the magnetoquasistatic regime based on the Laplace equation. Inside the objects, where the wave equation governs the field distribution, the currents are assumed to have a small penetration depth, allowing for the analytical simplification of the field components, which become decoupled at the surface. This approximation, which is valid across the entire frequency spectrum because of the high permeability and conductivity, avoids the necessity of using ellipsoidal wave functions and results in a considerable saving of computational time. Numerical results favorably compare with numerical and experimental data, which proves the usefulness of our method to model UXOs in clutter-contaminated soils. Finally, the optimization approach used to match our numerical predictions with experimental data demonstrates the possibility of remotely inferring the material properties of objects.

Combining dipole and mixed model approaches for UXO discrimination

A multi dipole (MD) model is combined with a statistical algorithm called the mixed model to discriminate between objects of interest, such as unexploded ordnance (UXO), and innocuous items. In the multi dipole model (an extended version of the single dipole model), electromagnetic induction (EMI) responses for bodies of revolution (BOR) are approximated with a set of dipoles placed along the axis of symmetry of the objects. The model accurately takes into account the scatterers heterogeneity along its axis of symmetry and is fast enough to invert digital geophysical data for discrimination purposes in real/near real time. Determining the amplitudes of the multi dipoles is an ill-posed problem that requires regularization. Obtaining the regularization parameters is not straightforward and in many cases is done via impractical supervised approaches. To overcome this problem, in this paper we combine a new statistical approach called the mixed model with the multi dipole model. Mixed modeling (MM) can be viewed as a generalization of the empirical Bayesian approach. It assumes that the forward model is not perfect: i.e., the model parameters (the amplitudes of the responding multi magnetic dipoles) contain random noise with zero mean and constant variance. Based on these assumptions, the method derives the regularization parameter from the variance of the least square error between the model and actual data using standard linear regression. Numerical results are presented to illustrate the theoretical basis and practical realization of the combined MD-mixed model (MD-MM) algorithm for UXO discrimination under real field conditions. In addition, a new condensed algorithm for determining the location and orientation of buried objects is introduced and tested against the ESTCP pilot discrimination study dynamic data set.

Detection of Multiple Subsurface Metallic Targets using EMI data

The detection of unexploded ordnance (UXO) in the presence of a discrete and large clutter is here investigated in the electromagnetic induction regime using a Newton method with no a priori information on the position or the strength of each object. The problem is formulated as a cost-function minimization on the difference in magnetic fields between the measured or synthetic data and their corresponding predictions. Both a bistatic and a monostatic operating modes are considered and applied to various geometrical configurations such as targets in close proximity or on top of each other. Measurement data from the TEMTADS sensor in a two-object configuration are also analyzed. The results illustrate the accuracy of the method in many situations, but also point out at some current limitations for which further improvements are suggested.

Underwater UXO detection and discrimination: understanding EMI scattering phenomena in a conducting environment

There are approximately one million acres of underwater lands at Department of Defense (DOD) and Department of Energy (DOE) sites that are highly contaminated with unexploded ordnance (UXO) and land mines. The detection and disposal of Underwater Military Munitions are more expensive than excavating the same targets on land. Electromagnetic induction (EMI) sensing has emerged as one of the most promising technologies for underwater detection. In order to explore the full potential of various EMI sensing technologies for underwater detection and discrimination, to achieve a high (~100%) probability of detection, and to distinguish UXO from non-UXO items accurately and reliably, first the underlying physics of EM scattering phenomena in underwater environments needs to be investigated in great detail. This can be achieved by using an accurate 3D numerical code, such as the combined method of auxiliary sources and thin skin depth approximation (MAS/TSA), the pseudospectral time-domain technique, finite element methods or other approaches. This paper utilizes the combined MAS/TSA, originally developed for detection and discrimination of highly conducting and permeable metallic objects placed in an environment with zero or negligible conductivity. Here, first the theoretical basis of the MAS/TSA is presented for metallic objects placed in an electrically conductive environment. Then numerical experiments are conducted for homogeneous targets of canonical (spheroidal) shapes subject to frequency- or time-domain illumination. The results illustrate coupling effects between the object and its surrounding conductive medium, particularly at high frequencies (early times for time-domain sensors), and the way this coupling depends on the distance between the sensor and the objects center.

EMI sensor positioning using a beacon approach

Discrimination of buried exploded ordnance by inversion of electromagnetic data requires accurate sensor positioning. There are many contaminated areas were dense forest or significant topographic variation reduces accuracy or precludes use of standard geo-location methods, such as satellite-based Global Positioning System (GPS) and laser tracking systems (e.g., Robotic Total Station, RTS), as these rely on line of sight. We propose an alternative positioning system that is based on a beacon principle. The system was developed to survey with the Man-Portable Vector (MPV) EMI sensor. The magnetic moment of the MPV transmitter can be detected at a relatively large distance. The primary field is measured from a portable base station comprised of two vector receivers rigidly attached to either ends of a 1.5 meter horizontal boom. Control tests showed that relative location and orientation could be recovered with centimeter positional and one degree angular accuracy within a 3-4-meter range and 60-degree aperture (relative to boom transverse direction), which is more than sufficient to cover any UXO anomaly. This accuracy level satisfies commonly accepted positional requirement for discrimination. The beacon positioning system can facilitate classification of munitions in any man-trafficable area and was successfully deployed at a field demonstration.

Combining NSMS and High-Quality MPV-TD Data for UXO Discrimination

In this paper, a new physics-based approach for estimating a buried objects location and orientation is combined with the normalized surface magnetic source (NSMS) model to analyze high-quality, high-density multiaxis data provided by the Man-Portable Vector (MPV) time domain (TD) sensor. The NSMS is a very simple and robust technique for predicting the EMI responses of various objects. It is applicable to any combination of magnetic or electromagnetic induction data for any arbitrary homogeneous or heterogeneous 3D object or set of objects. The physics-based approach to estimate location assumes that the target exhibits a dipolar response and uses only two global values, the magnetic field vector H and the scalar magnetic potential psi, reconstructed at a set of points in space. To demonstrate the applicability of the NSMS, we first compare its predictions with dynamic MPV-TD measurements and then present the results of a blind-test analysis using multiaxis static MPV-TD data sets.

Homemade explosives in the subsurface as intermediate electrical conductivity materials: a new physical principle for their detection

Detection of homemade explosive (HME) containing ammonium nitrate (AN) in the subsurface is of great interest to the US military and its coalition partners. Due to the hygroscopy of AN, this HME is expected to be an intermediate electrical conductivity material (IECM), defined here as one having electrical conductivity greater than soils, which have conductivities 0.1 to 1000 mS•m−1 but less than metals, which have electrical conductivities on the order of 10 MS•m−1. Our preliminary experimental and numerical modeling have established that AN-containing HME in the subsurface can, in all likelihood, be detected by electromagnetic exploration geophysics techniques, specifically by ground penetrating radar (GPR) and by electromagnetic induction (EMI). The electromagnetic induction signatures of HME for these techniques are distinctive. For example, in the case of EMI, the maximum quadrature response frequencies for IECM targets have been found to be greater than 100 kHz.