Norbert Geng

Multilevel fast-multipole algorithm for scattering from conducting targets above or embedded in a lossy half space

An extension of the multilevel fast multipole algorithm (MLFMA), originally developed for targets in free space, is presented for the electromagnetic scattering from arbitrarily shaped three-dimensional (3-D), electrically large, perfectly conducting targets above or embedded within a lossy half space. We have developed and implemented electric-field, magnetic-field, and combined-field integral equations for this purpose. The nearby terms in the MLFMA framework are evaluated by using the rigorous half-space dyadic Greens function, computed via the method of complex images. Non-nearby (far) MLFMA interactions, handled efficiently within the multilevel clustering construct, employ an approximate dyadic Greens function. This is expressed in terms of a direct-radiation term plus a single real image (representing the asymptotic far-field Greens function), with the image amplitude characterized by the polarization-dependent Fresnel reflection coefficient. Examples are presented to validate the code through comparison with a rigorous method-of-moments (MoM) solution. Finally, results are presented for scattering from a model unexploded ordnance (UXO) embedded in soil and for a realistic 3-D vehicle over soil.

Ultra-wide-band synthetic-aperture radar for mine-field detection

A full-wave model is developed for electromagnetic scattering from buried and surface land mines (both conducting and plastic), taking rigorous account of the lossy, dispersive, and potentially layered properties of soil. The (polarimetric) theoretical results are confirmed via synthetic-aperture radar (SAR) measurements, performed using the US Army Research Laboratorys BoomSAR, with which fully polarimetric ultra-wide-band (50-1200 MHz) SAR imagery is produced. The SAR system is used to acquire a large database of imagery, including a significant distribution of naturally occurring clutter. Several techniques are used for mine detection with such data, including several detectors that are based on target features gleaned from the modeling, as well as a matched-filter-like detector that directly incorporates the target signatures themselves. In addition, the theoretical model is used to predict wave phenomenology in various environments (beyond the limited range of parameters that can be examined experimentally). Since the efficacy of radar-based subsurface sensing depends strongly on the soil properties, we perform a parametric study of the dependence of such on the target RCS, and on possible landmine resonances.

Classification of landmine-like metal targets using wideband electromagnetic induction

In their previous work, the authors have shown that the detectability of landmines can be improved dramatically by the careful application of signal detection theory to time-domain electromagnetic induction (EMI) data using a purely statistical approach. In this paper, classification of various metallic land-mine-like targets via signal detection theory is investigated using a prototype wideband frequency-domain EMI sensor. An algorithm that incorporates both a theoretical model of the response of such a sensor and the uncertainties regarding the target/sensor orientation is developed. This allows the algorithms to be trained without an extensive data collection. The performance of this approach is evaluated using both simulated and experimental data. The results show that this approach affords substantial classification performance gains over a standard approach, which utilizes the signature obtained when the sensor is centered over the target and located at the mean expected target/sensor distance, and thus ignores the uncertainties inherent in the problem. On the average, a 60% improvement is obtained.

On the low-frequency natural response of conducting and permeable targets

The low-frequency natural response of conducting, permeable targets is investigated. The authors demonstrate that the source-free response is characterized by a sum of nearly purely damped exponentials, with the damping constants strongly dependent on the target shape, conductivity, and permeability, thereby representing a potential tool for pulsed electromagnetic induction (EMI) identification (discrimination) of conducting and permeable targets. This general concept is then specialized to the particular case of a body of revolution (BOR), for which the method-of-moments (MoM)-computed natural damping constants from several targets are compared with measurements. Moreover, theoretical natural (equivalent) surface currents and damping coefficients are shown for other targets of interest. Finally, the authors investigate the practical use of such natural signatures in the context of identification, wherein Cramer-Rao bound (CRB) studies address signal-to-noise ratio (SNR) considerations.

Wide-band electromagnetic scattering from a dielectric BOR buried in a layered lossy dispersive medium

A method of moments (MoM) analysis is developed for electromagnetic scattering from a dielectric body of revolution (BOR) embedded in a layered medium (the half-space problem constituting a special case). The layered-medium parameters can be lossy and dispersive, of interest for simulating soil. To make such an analysis tractable for the wide-band (short-pulse) applications of interest here, we have employed the method of complex images to evaluate the Sommerfeld integrals characteristic of the dyadic layered-medium Greens function. Example wide-band scattering results are presented, wherein fundamental wave phenomenology is elucidated. Of particular interest, we consider wide-band scattering from a model plastic mine, buried in soil, with the soil covered by a layer of snow.

Method of moments analysis of electromagnetic scattering from a general three‐dimensional dielectric target embedded in a multilayered medium

The method of moments (MOM) is applied to the problem of electromagnetic scattering from general three-dimensional dielectric targets in an arbitrary multilayered environment. The dyadic multilayered Greens function is computed via the method of complex images, and the Galerkin MOM solution is effected by employing triangular patch basis functions. Several example frequency and time domain results are presented, with application to radar-based sensing of plastic land mines.

Ultrawide-band synthetic aperture radar for detection of unexploded ordnance: modeling and measurements

Electromagnetic (EM) scattering from subsurface unexploded ordnance (UXO) is investigated both theoretically and experimentally. Three EM models are considered: the multilevel fast multipole algorithm (MLFMA), the method of moments (MoM), and physical optics (PO). The relative accuracy of these models is compared for several scattering scenarios. Moreover, the model results are compared to data measured by an experimental synthetic aperture radar (SAR) system, SAR images have been generated for subsurface UXO targets, in particular 155-mm shells. We compare SAR images from the measured data with theoretical images produced by the MoM and PO simulations, using a standard back-projection imaging technique. In addition to such comparisons with measurement, we consider additional buried-UXO scattering scenarios to better understand the underlying wave phenomenology.

On the resonances of a dielectric BOR buried in a dispersive layered medium

A method-of-moments (MoM) analysis is applied to the problem of determining late-time resonances of dielectric bodies of revolution buried in a lossy layered medium, with application to plastic-land-mine identification. To make such an analysis tractable, we have employed the method of complex images to evaluate the layered-medium Greens function. The application of this method to resonant structures characterized by complex resonant frequencies, introduces numerical issues not manifested at real frequencies (i.e., for driven problems) with such discussed here in detail. Numerical results are presented for several buried targets in which we demonstrate, for example, the spiraling character of the resonant frequencies of particular targets as a function of the target depth.

Wideband electromagnetic induction for metal-target identification: theory, measurement, and signal processing

A principal problem with traditional, narrowband EMI sensors involves target identification. As a consequence, in minefield or unexploded ordinance (UXO) detection, for example, each piece of buried metal must be excavated, causing significant false alarms in regions littered with anthropic clutter. Therefore, the principal challenge for the next generation of EMI sensors is development of electronics and algorithms which afford discrimination. To this end, in this paper we operate in the frequency domain, considering wideband excitation and utilize the complex, frequency-dependent EMI target response as a signature. To test the signature variability of different metal types and target shapes, as well as for calibration of an actual sensor, we have developed a full-wave model for the analysis of wideband EMI interaction with highly (but not perfectly) conducting and permeable targets. In particular, we consider targets which can be characterized as a body of revolution, or BOR. The numerical algorithm is tested through use of a new wideband EMI sensor, called the GEM-3. It is demonstrated that the agreement between measurements and theory is quite good. Finally, we consider development of signal processing algorithms for the detection and identification of buried conducting and permeable targets, using wideband data. The algorithms are described and then tested on data measured using the GEM-3, with results presented in the form of contour plots as a function of the number of discrete frequencies employed.

Wide-area detection of land mines and unexploded ordnance

Advanced electromagnetic modelling tools are discussed, focused on sensing surface and buried land mines and unexploded ordnance, situated in a realistic soil environment. The results from these forward models are used to process scattered-field data, for target detection and identification. We address sensors directed toward the wide-area-search problem, for which one is interested in detecting a former mine field or bombing range. For this problem class we process data measured from an actual airborne radar system. Signal-processing algorithms applied include Bayesian processing and a physics-based hidden Markov model.