Thomas H. Bell

Subsurface discrimination using electromagnetic induction sensors

This paper reviews the problem of subsurface discrimination using electromagnetic induction (EMI) sensors. Typically, discrimination is based on differences in the multiaxis magnetic polarizability between different objects. They review work on frequency and time domain systems, and their interrelationship. They present the results of comprehensive measurements of the multiaxis EMI response of a variety of inert ordnance items, ordnance fragments, and scrap metal pieces recovered from firing ranges. The extent to which the distributions of the eigenvalues of magnetic polarizability for the different classes of objects do not overlap establishes an upper bound on discrimination. For various reasons, the eigenvalues cannot always be accurately determined using data collected above a buried target. This tends to increase the overlap of the distributions, and hence degrade discrimination performance.

Electromagnetic induction spectroscopy for clearing landmines

An estimated 110 million landmines, mostly antipersonnel mines laid in over 60 countries, kill or maim over 26000 people a year. One of the dilemmas for removing landmines is the amount of false alarms in a typical minefield. Broadband electromagnetic induction spectroscopy (EMIS) is a promising technology that can both detect and identify buried objects as landmines. By reducing the number of false alarms, this approach significantly reduces costs associated with landmine removal. Combining the EMIS technology and a broadband EMI sensor, the scientific phenomenology that has potential applications for identifying landmines, unexploded ordnance, and hidden weapons at security checkpoints can now be explored.

Simple phenomenological models for wideband frequency-domain electromagnetic induction

The authors propose three phenomenological models for wideband electromagnetic induction (EMI) response of buried conductors, such as unexploded ordnance (UXO) or metal parts in landmines. The models are based on analytic solutions for spheres, cylinders, and wire loops, and produce physically reasonable predictions for a variety of targets at all frequencies of interest including matches to theory in the low- and high-frequency limits. All three produce excellent fits to test data and run quickly enough to be of practical use in data inversion schemes. The authors present a three-parameter model capable of exactly matching permeable spheres and cylinders, a four-parameter version which adds the capability to match wire loops, and a five-parameter version which adds the capability to match signals due to driving bands, a feature found only on UXO. Driving bands, also called rotating bands, are soft metal rings near the tail of a projectile designed to engage rifles in the gun bore when the projectile Is fired. The author observe that driving bands produce a distinctive loop-like signal in EMI spectra, possibly because they are in the shape of a loop and typically have much greater conductivity than the body of the UXO. They demonstrate that the five-parameter model is capable of accurately fitting this signal and expressing its presence or absence through model fit parameters.

Time and Frequency Domain Electromagnetic Induction Signatures of Unexploded Ordnance

This paper documents some of the progress that has been made in recent years in the application of electromagnetic induction (EMI) technology to the problem of discriminating between buried unexploded ordnance and clutter items such as exploded ordnance fragments or scrap metal. EMI classification of an unknown subsurface target is based on estimating the targets magnetic polarizability tensor from data collected above the ground. One can discriminate between different targets only if their polarizability tensors are sufficiently different. In this paper, we review the relationship between the time and frequency dependence of the polarizability tensor, evaluate the relative information content of the time and frequency domain signatures, and discuss how the sensor response affects signature measurement fidelity. Our analysis centers on simple parametric representations for the time and frequency domain EMI signatures that have been synthesized from extensive empirical studies of the EMI response of ordnance and clutter items. There are three basic parameters (amplitude factor, time constant and demagnetization factor) for each of the targets principal axes. They are related to the physical characteristics of the target and can be used for classification and discrimination.

EMI Array for Cued UXO Discrimination

Abstract : A vehicle-towed array of time-domain electromagnetic sensors was designed and operated to optimize the classification of buried munitions from ancillary metallic debris and clutter. The array was designed to combine the data quality advantages of a gridded survey with the coverage efficiencies of a vehicular system. The design goal for this system was to collect data equal, if not better, in quality to the best gridded surveys while prosecuting many more targets each field day. In order to separate out the intrinsic target response properties from sensor/target geometry effects, the measured signature is inverted to estimate principal axis magnetic polarizabilities using a standard induced dipole response model. The technology was validated through two blind tests conducted at the Aberdeen Proving Ground Standardized UXO Test Site and as part of the ESTCP UXO Classification Study at the former Camp San Luis Obispo. The performance metrics used to monitor the success of the technology relate to production rate, accuracy of inverted features, analysis time, correct classification, and ease of use.

Discriminating capabilities of multifrequency EMI data

Although commercially available geophysical sensors are capable of detecting UXO at nominal burial depths, they cannot reliably discriminate between UXO and clutter. As a result, an estimated 75% of remediation funds are spent on nonproductive excavations. During the past few years, we have been studying the merits of using multifrequency EMI data for discriminating between UXO and non-UXO targets and believe the method has tremendous potential. The EMI spectral response of an object is a function of its electrical conductivity, magnetic permeability, shape, size, and orientation relative the primary exciting field. By measuring a targets spectral response, we obtain its characteristic frequency-dependent signature.

Source separation using sparse-solution linear solvers

An algorithm is proposed to enumerate, locate and characterize individual signal sources given observation of their combined signals. No a-priori estimate for the number of sources is required. We assume a forward model exists, and that superposition holds, i.e. coupling between sources is ignored. A system of linear equations y=Ax is set up in which columns of matrix A contain expected signals from a large number of hypothesized sources, and y contains the observed signal. Recently-developed solvers designed for linear systems with sparse non-negative solutions make this approach feasible even when large numbers of sources are involved. With each iteration, the collection of hypothesized sources is refined using a Harmony Search algorithm. Application is demonstrated on the problem of locating multiple buried conductors based on electromagnetic induction (EMI) signals observed at ground surface.

Characterization of a GEM-3 array for UXO classification

We have designed and built a non-synchronous, sequential array of GEM-3 sensors for use with the Multi-sensor Towed Array Detection System (MTADS) with support from ESTCP. The roughly 2-m square array consists of three, 96-cm diameter GEM-3s in a triangular configuration. The GEM drive electronics have been modified to produce a substantially higher transmit moment, and thus increased sensitivity, than the standard GEM-3. The individual sensors transmit a composite waveform made up of ten frequencies from 30 Hz to 48 kHz for a single 1/30 s base period. Sequential operation allows two of these base periods for deconvolution and output of the frequency-dependent response from each GEM-3. After allowing for a short coil settling time between sensors, we achieve an array sampling rate of just over 9 Hz. Coupled with our standard survey speed of 3 mph, this results in a down-track sampling spacing of ~15 cm. The cross-track spacing is 50 cm. We have characterized these sensors at our Blossom Point test site. The static and dynamic response of the array to a variety of ordnance, ordnance simulants, and scrap is presented with consideration given to both detection and classification.

Extremely Low Frequency Response (Below 30 Hz) of UXO-Like Objects

Extremely low frequency measurements, below 30 Hz, of solid, thin-, and, thick-walled steel (permeable) cylinders with length-to-diameter ratios of approximately 4 are described and compared with the predicted response computed using a frequency domain finite element method (FDFEM). Measurements were made using a conventional EMI test setup consisting of a Hewlett Packard 89410 vector signal analyzer, rectangular transmitting and a figure-eight (bucked) receiving coil, along with appropriate transmitter and receiver coil amplifiers. All cylinders were measured with the predominant component of the excitatory magnetic field both aligned with and orthogonal to (two distinct measurements) the cylinders axis. Measurements were made with and without a centered copper ring on the cylinders. The ring simulates the so-called rotating bands on actual UXO. Not surprisingly, we observed that the quadrature peak of the response shifts down in frequency much more when the axis of the ringed cylinder is aligned with the excitatory magnetic field than when perpendicular to it. Our measurements indicated that the real part of the response of the smallest cylinders measured asymptotically approaches its DC value around 1 Hz while the largest of the cylinders measured does not asymptote until well below 1 Hz. It appears that target information that may be crucial for discrimination purposes, especially for larger targets, exists at frequencies well below 30 Hz. Extremely low frequency measurements, especially with data averaging (stacking), can be a rather time consuming process, and therefore it is not likely that such measurements can be made from a moving platform. However, once an object of interest has been detected, the target can be reacquired and the measurement taken with the sensor stationary with respect to the target (sometimes referred to as a qued approach). As our measurements and simulations indicate, the qued method may be necessary if large solid UXO are to be distinguished from large thin-walled clutter objects.

Progress toward an electromagnetic induction mine discrimination system

In this paper we discuss fundamental considerations in the design of an electromagnetic induction (EMI) sensor. Simple circuit representations of pulsed and continuous wave EMI systems are presented and the analysis of these circuits leads one to certain conclusions regarding optimal (good) sensor design. Findings reported here are gathered from experimental research conducted over the past year and directed toward the development of an EMI system that not only has reasonable sensitivity but also has the ability to capture a targets low frequency response characteristics. The later capability is important when attempting to discriminate between low metallic content landmines and metallic clutter.