We introduce a frequency-domain electromagnetic induction (EMI) instrument for detection and classification of objects with either high ($\sigma > 10^{5}~\textrm {S/m}$) or intermediate ($1 < \sigma < 10^{5}~\textrm {S/m}$) electrical conductivity. While high conductivity metallic targets exhibit a quadrature peak response for frequencies in a traditional EMI regime under 100 kHz, the response of intermediate conductivity objects manifests at higher frequencies, between 100 kHz and 15 MHz. Materials such as carbon fiber or conducting salt solutions exhibit conductivities in this intermediate range and are undetectable by traditional low-frequency EMI instruments. To detect these intermediate conductivity targets, we developed a high-frequency EMI (HFEMI) instrument with a frequency range extended to 15 MHz. The HFEMI instrument requires novel hardware considerations, coil design, and data processing schemes. Most importantly, the wire lengths of transmit and receive coils are shorter than those of traditional frequency EMI sensors, so that the phase on the transmit and receive coils is nearly constant. We present the hardware and software aspects of the HFEMI instrument along with preliminary data, demonstrating its ability to detect intermediate conductive objects.

We demonstrate in detail a semisupervised scheme to classify unexploded ordnance (UXO) by using as an example the data collected with a time-domain electromagnetic towed array detection system during a live-site blind test conducted at the former Camp Butner in North Carolina, USA. The model that we use to characterize targets and generate discrimination features relies on a solution of the inverse UXO problem using the orthonormalized volume magnetic source model. Unlike other classification techniques, which often rely on library matching or expert knowledge, our combined clustering/Gaussian-mixture-model approach first uses the inherent properties of the data in feature space to build a custom training list that is then used to score all unknown targets by assigning them a likelihood of being UXO. The ground truth for the most likely candidates is then requested and used to correct the model parameters and reassign the scores. The process is repeated several times until the desired statistical margin is reached, at which point a final dig is produced. Our method could decrease intervention by human experts and, as the results of the blind test show, identify all targets of interest correctly while minimizing false-alarm counts.

We introduce a fast and accurate numerical technique for the solution of electromagnetic induction sensing problems called the orthonormalized volume magnetic source model. The model assumes that the secondary magnetic field measured by a sensor originates from a set of magnetic dipole sources distributed over a volume that coincides with the interrogated area. The Green functions associated with the responding sources are turned into an orthonormal basis using a generalization of the Gram-Schmidt method, enabling one to determine the sources' strengths directly from measured data without having to invert large and potentially ill-conditioned matrices. The method treats multitarget cases naturally and robustly. Several examples are presented to illustrate the applicability of the method in the discrimination of unexploded ordnance (UXO). In particular, we analyze data taken by the Time-Domain Electromagnetic Multisensor Towed Array Detection System sensor array at a test stand and during a blind test administered at a UXO live site. The method is highly successful in distinguishing UXO from among other UXO and from accompanying clutter.

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.

The modeling of unexploded ordnances in the electromagnetic induction regime (from tens of hertz to a few kilohertz) is carried out in the ellipsoidal coordinate system, thus presenting an important generalization of the existing dipole model or spheroidal approach. Ellipsoidal geometries are of interest because of their ability to more accurately model real 3D objects while retaining the appeal of an analytical solution. Computation speed is minimized here by assuming objects of high permeability and conductivity, allowing for the use of the small penetration approximation, and avoiding the necessity of solving the wave equation using ellipsoidal wave functions inside the object. Simulations are compared with both existing numerical solutions and with measured data on fabricated ellipsoids, and prove the validity of our model.

In this paper, a new physics-based approach for estimating a buried object's 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.

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.

Two different supervised learning algorithms, support vector machine (SVM) and neural networks (NN), are applied in classifying metallic objects according to size using the expansion coefficients of their magneto-quasistatic response in the spheroidal coordinate system. The classified objects include homogeneous spheroids and composite metallic assemblages meant to resemble unexploded ordnance. An analytical model is used to generate the necessary training data for each learning method. SVM and NN are shown to be successful in classifying three different types of objects on the basis of size. They are capable of fast classification, making them suitable for real-time application. Furthermore, both methods are robust and have a good tolerance of 20-dB SNR additive Gaussian noise. SVM shows promise in dealing with noise due to uncertainty in the object's position and orientation.

We propose a spheroidal mode approach to characterize the electromagnetic induction (EMI) response of buried objects, assumed to be much more conductive than their environment. Both the excitation and the response are formulated as the linear superpositions of basic spheroidal modes. The scattering coefficients characterize objects, regardless of their geometrical complexity and material inhomogeneity, due to the orthogonality of the spheroidal modes. The ill-conditioning encountered in retrieving the scattering coefficients is dealt with by mode truncation and Tikhonov regularization. The approach is tested for both simulated and measured data, and the retrieval results show encouragingly that only few excitation and response modes effectively represent the EMI response of the objects. The proposed approach is therefore promising in the detection and classification of buried objects

Electromagnetic induction (EMI) is a popular technique to detect and discriminate buried unexploded ordnance (UXO). However, modeling of the EMI response from many types of UXO is difficult due to the small skin depth of the interior fields. In grid-based numerical methods, meshing the target volume or surface to resolve the skin depth is often highly impractical, yet a failure to do so yields inaccurate results. This paper addresses the problem with a time-domain hybrid technique based on thin-skin approximation (TSA) that is very accurate for small skin depths. The TSA method is applied to axisymmetric problems and is shown to be both fast and accurate when the skin depth is small. The method is compared with analytical results, and excellent agreement is obtained. For magnetic materials (such as steel), the TSA method is accurate for the complete time-domain EMI response. In such cases, the TSA method provides an improved accuracy along with an order-of-magnitude reduction in CPU time compared to a dense-mesh finite-element method (FEM). For nonmagnetic materials, the TSA loses accuracy as time progresses and must be combined with a coarse-mesh FEM. In such cases, the combined method still provides greater accuracy with comparable CPU time.

In practice, most signal processing strategies for discrimination of buried objects are clutter limited. This applies even to discrimination of shallow sizable metallic objects, such as unexploded ordnance (UXO), which are to be found predominantly in the top meter of soil. The environment typically features widespread metallic clutter from detonated ordnance or other sources. Such fragments can be numerous and are often shallower than the objects of interest. Currently, the preeminent remote sensing mode for buried UXO is ultrawideband electromagnetic induction (EMI), operating over part or all of the band from some tens of hertz up to perhaps hundreds of kilohertz. Particularly because EMI fields fall off sharply with range, signals from shallow clutter may be relatively strong and can easily obscure essential scatterer signatures. To treat this, a rational theory of EMI scattering from widespread metallic clutter is formulated and tested. For dense, well-distributed clutter, analytical rules are derived for dependence of signal strength on sensor elevation, under various fundamental excitation types. For more erratic, sparse clutter distributions, signal statistics from Monte Carlo simulations show patterns like those from the analytical rules. The dependence of clutter signal magnitude on antenna elevation is determined for both thin surface layers and for volume layers of widespread small items, and for both dense and sparse clutter distributions. These are contrasted with the patterns expected from single, larger, discrete objects of interest, and the contrast is exploited in discrimination exercises for the screening problem. For sparse clutter distributions, results from inversion processing formulations that account for the patterns of clutter statistics are compared to simple least squares treatments.

Data services for the grid have focussed so far primarily on virtualising access to distributed databases, and encapsulating file location. However, orchestration of services requires richer information semantics than these mechanisms provide. Service inputs and outputs must be semantically matched, or characterised in order that sensible transformations may be performed. In many domains important information structures must be aggregated across multiple files, and numerous legacy file formats obscure the natural logical structure of information types. We present a solution for constructing semantic data services for an earth-sciences data grid (the UK NERC DataGrid). A semantically-rich data model is developed, drawing on components from external ontologies. A 'storage descriptor' provides the mechanism for mapping legacy file-based storage onto data model instances. Finally, data services may be built on top of the data model to expose a semantic view of the data irrespective of the underlying file storage details. Our approach is similar to wrapper/mediator architectures for integrating database management systems.

In this paper, the coupling and close-proximity effects arising between highly conducting and permeable metallic objects are exposed and analyzed, for the electromagnetic induction (EMI) frequency range (from tens of hertz up to several hundreds of kilohertz). To understand the physics of the interaction phenomena, a numerical technique is applied, consisting of the full method of auxiliary sources (MAS) at low frequencies and a combination of the MAS with thin-skin approximation (TSA) at high frequencies. Both numerical MAS-MAS/TSA and experimental studies have shown that the scattered field from a heterogeneous target generated as a simple superposition of independent responses from each part can be very different from the field determined from whole object with full internal interaction. A new numerical technique for fast and accurate representation of EMI responses for heterogeneous objects is pursued here, applicable to any three-dimensional heterogeneous object placed in an arbitrary time-varying EMI field. First, any primary magnetic field input is decomposed into the spheroidal modes over a fictitious surface surrounding the object. Then, for each input spheroidal mode, the full EMI problem including all interaction is solved using the MAS-MAS/TSA technique, and each modal response is reproduced using a compact reduced set of sources (RSS). Finally, the total response from the given target for any other excitation can be synthesized simply by calculating that primary field's constituent spheroidal modes and combining their stored responses. Several numerical examples are designed to show how an object's electromagnetic parameters, geometry, distance between objects, antenna positions, and orientations relative to the object affect the coupling. Comparisons between numerical and measured data for a machined composite object and for an actual unexploded ordnance demonstrate the superior accuracy and applicability of the MAS-MAS/TSA RSS model over simple dipole approximations, for certain classes of heterogeneous objects.

Current idealized forward models for electromagnetic induction (EMI) response can be defeated by the characteristic material and geometrical heterogeneity of realistic unexploded ordnance (UXO). A new, physically complete modeling system was developed that includes all effects of these heterogeneities and their interactions within the object, in both near and far fields. The model is fast enough for implementation in inversion processing algorithms. A method is demonstrated for extracting the model parameters by straightforward processing of data from a defined measurement protocol. Depending on the EMI sensor used for measurements, the process of inferring model parameters is more or less ill-posed. More complete data can alleviate the problem. For a given set of data, special numerical treatment is introduced to take the best advantage of the data and obtain reliable model parameters. The resulting fast model is implemented in a pattern matching treatment of measurements by which signals from a UXO are identified within a series of those from unknown targets. Preliminary results show that this fast model is promising for use in processing of this kind. The inherent difficulties of target identification are examined, and solutions for resolving these difficulties are discussed.

In this paper, a new discrimination procedure is presented to enhance classification of buried metallic object. This algorithm is based on a standardized source set (SSS) approximation, applicable for an arbitrary highly conducting and permeable metallic objects placed in a low frequency (from 10's of Hertz up to several 100's of kHz) time varying electromagnetic field. The method treats accurately all near field, heterogeneity, and internal interaction effects. In the SSS approach, any input primary magnetic field is represented as a sum of magnetic fields produced by a set of sources distributed over on an auxiliary surface outside the fictitious surface. The object's response corresponding to unit amplitudes of any of these input field sources is likewise quantified in terms of a set of (responding) sources, which can be derived from measured data. Thereafter, the object's response to any excitation can be expressed just by different superpositions of these standardized inputs. The spatial distribution and frequency dependence features of responding equivalent sources are analyzed and used for target discrimination. The numerical results are given for an actual unexploded ordinance (UXO)

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.

Operating as low as tens of hertz and as high as hundreds of kilohertz, new broadband electromagnetic induction (EMI) sensors have shown promise for classification of unseen buried metallic objects. The three-dimensional (3-D) and bodies-of-revolution (BOR) numerical studies reported here are designed to explain key scattering sensitivities that may either be useful in or may limit object classification capability. The target is excited either by a spatially uniform oscillating primary magnetic field or by the oscillating field from a loop antenna. The problem is formulated in terms of Poison's equation for scalar potential outside the object, where conductivity and electric field values are low and consequent conduction currents are generally negligible. The Helmholtz equation for vector potential applies inside the highly conducting and permeable object. In both regions, the electromagnetic phenomena of interest are magneto-quasi-static (MQS). The simulation algorithm uses the method of auxiliary sources (MAS), with auxiliary magnetic charges and auxiliary magnetic current elements distributed on auxiliary surfaces. These surfaces generally conform to but do not coincide with physical surfaces, providing extraordinarily efficient and accurate 3-D solutions. Comparisons to available analytical solutions and experimental data validate the solutions. The simulations and data illuminate broadband MQS scattering phenomenology for both magnetic and nonmagnetic metallic objects. Distinctive sensitivities are shown and signature effects analyzed relative to the scatterer's shape and aspect ratio, orientation, sharp points and edges, finite wall thickness in hollow bodies, and compound structure in which a geometrically complex body consists of a number of distinct sections, e.g., fins.

Operating in the magnetoquasistatic regime (a few hertz to perhaps a few 100 kHz), electromagnetic induction (EMI) sensing has recently emerged as one of the most promising avenues for discrimination of subsurface metallic objects, e.g., unexploded ordnance. The technique of thin-skin approximation (TSA) was devised to deal with numerical problems caused by the rapid decay of fields beneath the scatterer's surface. The rather nonintuitively broad applicability and specific error patterns of the TSA formulation are explained here by theoretical analysis based on analytical solutions and approximate Monte Carlo simulation. In the limiting case of infinitesimal skin depth (EMI perfect reflection), the scatterer aspect ratio (AR) is inferred without regard to metal type. Alternatively, the AR of some homogeneous magnetic objects is inferred from the pattern of transverse to axial response ratio over the entire EMI ultrawideband. Use of the method in inversions for electromagnetic parameters reveals fundamental nonuniqueness problems and shows their basis, which is not dependent on the method of forward solution.

Cleanup of subsurface metallic objects such as unexploded ordnance (UXO) constitutes an urgent problem worldwide. The heart of the problem is discrimination, as opposed to detection. Ultra-wideband electromagnetic induction sensors (UWB EMI), operating from a few Hz up to 100s of kHz, have shown considerable promise in subsurface discrimination of metallic objects. Unfortunately, a great many objects, including widespread clutter items, produce very broad, smooth EMI signal patterns, over a number of decades of frequency. Shape identification is complicated by the sensitivity of EMI fields to metal type. UWB ground penetrating radar (GPR) has also shown definite discrimination capability for characterizing subsurface metallic targets. Uninfluenced by metal type, GPR is capable of registering complex natural resonances from which target length can be estimated. Further, examination of the spatial patterns of GPR signals can indicate the (X,Y,Z) locations of targets, even of multiple targets present simultaneously in the incident beam. In this paper we consider potential collaborative roles of UWB GPR and UWB EMI for discrimination of multiple subsurface metallic objects. Rigorous 3-D FDTD models demonstrate GPR's ability to estimate target positions, orientations, and length even when reflections overlap. These data can then be used to constrain inversion of UWB EMI patterns. Processing of EMI measurements based on prior estimates of object location and orientation successfully extracts distinct frequency response signatures for two very closely spaced objects.

Discrimination of buried unexploded ordinance (UXO) from innocuous buried items remains a challenging, top priority problem for the electromagnetic induction (EMI) sensing community. In general, classification is an inverse problem, requiring very fast and accurate representation of the target response. To address this critical issue, this paper presents a very fast, rigorous way to compute EMI scattering from a realistically complex, composite target. Full interaction between all parts of the object are included in the calculations. The method is based on a hybrid of the full method of auxiliary source (MAS) and the MAS-thin skin depth approximation formulation (MAS-TSA), together with new modal decomposition and reduced source set techniques. For general excitation, a primary field is decomposed into the fundamental spheroidal modes on a fictitious spheroid surrounding a real target. Finally the total response from the target is reproduced using only a few auxiliary magnetic charges. A least square minimization is used for discrimination an unseen object's orientation and position. Numerical results are given and compared with experimental data.

Detection and identification of buried unexploded ordinance (UXO) is an emerging problem worldwide. Recent ultra wideband (UWB) field tests between 10s of MHz and 100s of MHz have demonstrated that certain of the target's dimensions can be estimated from analysis of complex natural resonances in the scattered signal. However, the problem becomes much more complicated at highly contaminated UXO sites where clutter items, from which subsurface UXO must be distinguished, appear simultaneously within the field of view of the sensor. This often occurs in realistic field conditions, where GPR discrimination capabilities are typically limited by ground clutter, coupling between antenna and ground, and limited view of the target due to innocuous items. Under extreme shielding by clutter, the incident field cannot excite strong currents on the target and in turn the scattered field from the object cannot easily be separated from the responses of the clutter. To investigate this, we pursue simulations here designed to test subsurface side-looking EM field scattering from multiple buried objects placed in a uniform ground. The numerical calculation is performed using the finite difference time domain (FDTD) method in conjunction with generalized perfectly matched layer GPML. The results are analyzed for a cylinder and plate placed in a uniform ground.

Estimating electric conductivity /spl sigma/ (S/m) and magnetic permeability /spl mu/ (F/m) is of great interest both for industry, mineral exploration, and for geophysical discrimination of buried objects such as unexploded ordnance (UXO). We present here a technique for inferring physical parameters of a metallic object in the EMI frequency range (from tens of Hz to several hundred kHz). Electric conductivity and magnetic permeability are inferred by an inversion algorithm operating on inphase and quadrature received components. The forward model is based on the BIE-TSA formulation, which works well over the majority of the EMI frequency range, especially for magnetic material. The formulation is organized so that most matrices related to object geometry need only be calculated once and the Jacobian matrix can be constructed easily from these matrices. Therefore, both forward solution and Jacobian matrix can be calculated quickly. For material with high magnetic permeability, forward solutions indicate that the scattered field is mostly only sensitive to the ratio of /spl sigma/ and /spl mu/. In this case the inversion algorithm becomes ill conditioned and some kind of regularization is needed. The performance of the inversion algorithm was studied under different kinds of regularization, via both theoretical analysis and numerical experiments. An optimized method for choosing regularization is suggested which may also benefit more general inverse problems.

A broadband, fully polarimetric ground penetrating radar (GPR) system has been applied for classification of buried unexploded ordnance (UXO) for the past few years. It utilizes both late-time and early-time signatures extracted from GPR data collected with multiple antenna positions and multiple scan orientations. Various field measurements were conducted from 1999 to 2001 at UXO sites that have quite different environmental conditions. Lessons learned from these tests have led to significant system improvements.

The detection and classification of unexploded ordnances (UXOs) is a difficult task, and it is even further complicated by the fact that the ground penetrating radar (GPR) antenna can significantly distort the scattering signal from the UXO. We consider the model of the real antenna which will be used in the numerical study of scattering from UXOs. We consider a rigorous finite difference time domain (FDTD) model of a fully polarimetric horn-fed bowtie (HFB) antenna and study how various modifications of the parameters of the antenna can affect it performance.

UWB electromagnetic induction (EMI) sensing, from 10s of Hz up to 100s of kHz, is emerging as one of the most promising remote sensing technologies for discrimination of subsurface metallic objects. Progress is urgently needed to distinguish dangerous objects, such as unexploded ordnance, from innocuous clutter. Development of EMI signal calibration, interpretation, processing, and inversion have all been impeded by the lack of rigorous, reliable analytical solutions for any scatterer shape other than the sphere. Here we test a number of new approximate solutions and determine that most canonical geometries and common, homogeneous material compositions can be treated adequately by the simple formulations proposed.

A new broadband electromagnetic (EMI) sensor, operating as lows as 10s of Hz and as high as 100s of kHz, has shown significant improvement for classification of buried metallic objects. EMI responses ("secondary" or scattered magnetic field) are characterized by two components, one inphase and another in phase quadrature with the primary field. Numerical and experimental investigations show that the frequency location of the quadrature peak in EMI scattered fields from metallic objects depends strongly on the major axis length ratio and on the object's orientation relative to the transmitted field. To illustrate potentially useful processing of EMI sensor data, this paper presents results of high fidelity numerical simulations to verify a theory for simple estimation of an object's aspect ratio based on the frequency location of the quadrature peak (permeable case). Results are shown for a permeable cylinder and spheroid.

Wideband electromagnetic induction (EMI) sensing shows increasing capability and promise for characterizing subsurface metallic objects, such as UXO. While EMI has some advantages over radar, such as superior penetration of moist soil, the field problem is still difficult due to the frequent occurrence of multiple targets in close proximity. The numerical modeling problem, even for a single object, is complicated by the fact that transmitted ("primary") fields typically penetrate the target, but will often only do so slightly. In most of the established numerical treatments, the scale of discretization is dominated either by the dimensions of the thin subsurface layer of electrical activity, or, more or less equivalently, by the range over which a Green's function decays, based on the characteristics of the metal. Resolution at this scale is often computationally prohibitive, particularly for magnetic materials, even though external fields of interest have only mild gradients. We approach the problem using the Thin Skin Depth Approximation (TSA). The TSA assumes an exponential form for the internal normal magnetic field component, as a function of distance inwards from the object surface. Despite the fact that it is designed to treat a state of affairs characteristic of relatively high EMI frequencies, results based on the TSA turn out to be accurate across the entire EMI band when the relative permeability of the scatterer material is high (e.g. as for steel).

Broad-band electromagnetic induction (EMI) methods are promising in the detection and discrimination of subsurface metallic targets. In this paper, the quasi-magnetostatic solution for a conducting and permeable prolate spheroid under arbitrary excitation by a time-harmonic primary field is obtained by using the separation of variables method with vector spheroidal wave functions. Numerical results for the induced dipole moments are presented for uniform axial and transverse excitations, where the primary field is oriented along the major and minor axis of the prolate spheroid, respectively. They show that the EMI frequency responses are sensitive to the orientation and permeability of the spheroid. An approximation is also developed that aims to extend the exact solution to higher frequencies by assuming slight penetration of the primary field into the spheroid. Under this approximation, a system of equations that refers only to the external field expansions is derived. It is shown that, for spheroids with high relative permeability, this approximation is in fact capable of yielding an accurate broad-band response even for highly elongated spheroids.

The Method of Auxiliary Sources (MAS) is formulated and applied to solution of wide-band electromagnetic induction problems involving highly conducting and possibly permeable metallic objects. Improved remote sensing discrimination of buried unexploded ordnance (UXO) motivates the study. The method uses elementary auxiliary magnetic charges and magnetic current elements to produce the unknown field. Auxiliary sources are located on virtual surfaces that usually conform to but do not coincide with the real surface of the object. Once the source coefficients are determined, the-secondary field can easily be found. The method involves no confrontations with source or Green's function singularities. It is capable of treating penetrable as well as nonpenetrable objects. Because the solution is composed of fields that automatically satisfy the governing equations, by construction, all approximation resides only in the enforcement of boundary conditions at matching (collocation) points. Accuracy in satisfying the boundary conditions can be evaluated explicitly using noncollocation points over the surface. This in turn allows one to identify problem areas on the surface and make intelligent adjustments of the source distributions, to improve solutions at minimal cost. A general 3D formulation is presented, and a version specialized to treat bodies of revolution is applied in the specific test cases discussed.

The problem of numerical modeling of electromagnetic induction (EMI) responses by metallic objects is complicated by the fact that transmitted fields may penetrate the target, but will often only do so slightly. The effect cannot be ignored, yet it is often grossly impractical to discretize the entire surface or volume of a target in space increments only on the order of a fraction of the skin depth. To deal with this problem, we retain a simple integral equation formulation in scalar potential for the region outside the target, where magnetic fields are quasi-static and irrotational. Within the target we apply only the divergence relation, /spl nabla//spl middot/H = 0. When the skin depth is small relative to the radius of curvature of the target (e.g., <0.1), we use the thin skin depth approximation (TSA), /spl part/H/sub n///spl part/n as /spl sim/-ikH/sub n/, just inside the target's surface, where k is the electromagnetic wavenumber inside the metal and n is the normal direction on the surface and pointing inside of metallic object. Examination of analytical solutions for the sphere suggests the parameter range in which this approximation might perform well and suggests ways of improving accuracy over an extended range. The fundamental TSA formulation appears to be relatively robust. Analysis indicates that it is insensitive to variation over the target's surface of primary field orientation relative to that surface, and that it is only dependent on the target's magnetic permeability through induction number. Implementing the TSA numerically, within the above divergence relation, allows us to express all quantities in terms of tangential magnetic field components and their tangential derivatives over the target surface. In principle, this closes the system completely in terms of the exterior scalar potential. Broad-band numerical simulations based on the TSA compare favorably with analytical and other numerical solutions.

An analytical solution is presented for the problem of magnetic diffusion into and scattering from a permeable, highly but not perfectly conducting prolate spheroid under axial excitation, expressed in terms of an infinite matrix equation. The spheroid is assumed to be embedded in a homogeneous nonconducting medium as appropriate for low-frequency, high-contrast scattering governed by magnetoquasistatics. The solution is based on separation of variables and matching boundary conditions where the prolate spheroidal wavefunctions with complex wavenumber parameter are expanded in terms of spherical harmonics. For small skin depths, an approximate solution is developed that avoids any reference to the spheroidal wavefunctions. The problem of long spheroids and long circular cylinders is solved by using an infinite cylinder approximation. In some cases, our ability to evaluate the spheroidal wavefunctions breaks down at intermediate frequencies. To deal with this, a general broadband rational function approximation technique is developed and demonstrated. We treat special cases and provide numerical reference data for the induced magnetic dipole moment or, equivalently, the magnetic polarizability factor.

An ultrawide-bandwidth (UWB) ground penetrating radar (GPR) was used to collect fully-polarimetric backscattered data from 10 to 800 MHz using a dual-polarization version of the previously developed dielectric-loaded horn-fed bow-tie (HFB) antenna. Special processing algorithms were developed to extract the polarization, orientation, depth, and length features of the target under investigation. The polarization and resonance features were utilized to discriminate subsurface ordnance from false-alarm objects that do not have elongated bodies. The classification of a specific type of unexploded ordnance (UXO) was also performed using the known length information. The processed results obtained from an initial blind field test show a very encouraging discrimination performance.

Polarimetric analysis of ground penetrating radar (GPR) backscatter offers a new means of discriminating subsurface metallic target shapes from one another. Such discrimination is urgently needed to distinguish buried unexploded ordnance (UXO) from other subsurface objects. To illuminate the underlying phenomenology of scattering from objects enveloped in soil, three-dimensional (3D) simulations are performed over a broad frequency band, characteristic of new low frequency GPRs. For moist soil, this means that the subsurface wavelength may range from a fraction of the target size to an order of magnitude larger With a transmitting antenna representation that produces typical subsurface GPR beam features, combined effects of positional, orientation, and frequency diversity are investigated. Despite long wavelengths, results show distinctive features in reflections obtained from contrasting example target shapes. Full polarimetric analysis suggests the capability for inferring the length of elongated targets, aspect ratio and rotational symmetry, and gross shape along the axis for either elongated or flattened bodies of revolution in problematical orientations.

Throughout the world, the problem of buried unexploded ordnance (UXO) poses an enormous, persistent, and expensive problem. While UXO generally consists of sizable bodies of ferrous metal and can therefore be detected, with current technology it is extremely difficult to distinguish them reliably from typically widespread pieces of clutter. Thus the problem is one of subsurface discrimination. The authors previous modeling work on scattering of ground penetrating radar (GPR) from metallic objects surrounded by an infinite soil-like medium has suggested the utility of a number of key discriminants in broadband fully polarimetric sensing. In particular, resonance structure, induced field rotation and ellipticity, and bistatic observation of scattered signals were shown to offer key information about target shape and size. The authors investigate the effects on signature features of the proximity of a ground surface to the target, for the common case of shallow burial (<1 m). Overall, their analyses suggest that the key discriminants seen in scattering in an infinite medium survive the complex interactions with the ground surface. In some instances, these revealing signatures appear to be strengthened by the presence of a nearby surface. Multiposition backscatter also allows fundamental inferences about target elongation and symmetry when those cannot be obtained from single position viewing.

A robust ground penetrating radar (GPR) signal processing approach is developed and applied to the sensing of surface soil and ice/water layers as well as near-surface buried objects. The principal technique relies on a reference set of waveforms, which are tested for optimal matching with measured radar reflections to be analyzed. In principle, the reference set can be based on measurements as well as on model output, with the latter employed. Even when layers are quite thin relative to the incident wavelength or pulse, the approach provides accurate information on layer characteristics, particularly thickness. The method assumes a well-defined transmit signal and hence is best used with antennas elevated shove the surface, In tests using UHF pulses on lab and field ice and on thawing soil, the system offers approximately an order of magnitude improvement in layer resolution relative to more traditional methods. Also, in the process of its signal-matching calculations, the procedures provide a numerical indication of the reliability of each result. In application to thawing soil, simulations suggest that one can address a wide variety of conditions using quite a limited set of reference signals. By detecting the thin-layer effect from soil over a buried metallic object, the system also locates near-surface targets when their reflections cannot be separated in time from ground surface returns. An alternative system also succeeds in detecting near-surface objects under the same conditions by detecting wavelet dispersion. This is done without reliance on specific details of transmit wavelet or reflected signals. A mine-like target is detectable in a wet clay soil when the ground is frozen but not when it is thawed.

This paper investigates the application of angular correlation function (ACF) processing for target detection when a metallic object beneath a randomly rough soil surface is sought by ground penetrating radar (GPR). ACF processing is an inherently coherent and multistatic approach. The author compares its results to those from candidate multistatic incoherent processing strategies. In 2D numerical simulations, the author assumes that the antennas are elevated above the soil surface, and that the only significant source of environmental randomness is the soil surface roughness. To expand the basis for the ACF, averaging is performed over both frequency and limited spatial shift. The author takes pains to use realistic GPR problem parameters, together with relevant and varied target geometries. Results are evaluated over an ensemble of geometrical realizations to gain some statistical picture of each method's behavior and performance. Under the parameter limitations applied, combined frequency and spatial averaging are required to produce recognizable ACF behavior. Contrary to expectations, the ACF processing performs best in the vicinity of the "memory line," not when it is avoided.

Two-dimensional electromagnetic scattering from a perfectly conducting target embedded near the randomly rough surface of an isotropic lossy dielectric is investigated. The randomly rough surface is illuminated by a finite width beam from an antenna in the free space above the surface, with off-normal incidence. Standard integral equation methods are applied and include all subsurface interactions between the object and rough surface. For a chosen embedded target, Monte Carlo simulations are performed for a selection of ensembles of rough surface types intended to be suggestive of natural ground. Far field scattering coefficient distributions and corresponding synthetic images suggest when the buried object should be discernible. Sensitivities are explored in terms of surface type, polarization of the incident field, depth and orientation of target, soil characteristics, incidence angle, and beamwidth. Many of the scattering features identified should also apply in 3D.

An experiment in which the third Stokes parameter thermal emission from a periodic water surface was measured is documented. This parameter is shown to be related to the direction of periodicity of the periodic surface and to approach brightnesses of up to 30 K at X-band for the surface used in the experiment. The surface actually analyzed was a "two-layer" periodic surface; the theory of thermal emission from such a surface is derived and the theoretical results are found to be in good agreement with the experimental measurements. These results further the idea of using the third Stokes parameter emission as an indicator of wind direction over the ocean.>