Anders Sullivan

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.

Multilevel fast multipole algorithm for general targets on a half-space interface

The multilevel fast multipole algorithm (MLFMA) is considered for scattering from an electrically large conducting or dielectric target resting on the interface of a dielectric half-space. We focus on analysis of the half-space Greens function such that it is computed efficiently and accurately, while retaining a form that is applicable to an MLFMA analysis. Attention is also directed toward development of a simple preconditioner to accelerate convergence of the conjugate-gradient solver. The utility of the model is examined for several applications, including scattering from an electrically large vehicle, trees, and rough dielectric interfaces in the presence of a dielectric half-space background.

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.

Blind backscattering experimental data collected in the field and an approximately globally convergent inverse algorithm

An approximately globally convergent numerical method for a 1D coefficient inverse problem for a hyperbolic PDE is applied to image dielectric constants of targets from blind experimental data. The data were collected in the field by the Forward Looking Radar of the US Army Research Laboratory. A posteriori analysis has revealed that computed and tabulated values of dielectric constants are in good agreement. Convergence analysis is presented.

Multi-aspect detection of surface and shallow-buried unexploded ordnance via ultra-wideband synthetic aperture radar

An ultra-wideband (UWB) synthetic aperture radar (SAR) system is investigated for the detection of former bombing ranges, littered by unexploded ordnance (UXO). The objective is detection of a high enough percentage of surface and shallow-buried UXO, with a low enough false-alarm rate, such that a former range can be detected. The physics of UWB SAR scattering is exploited in the context of a hidden Markov model (HMM), which explicitly accounts for the multiple aspects at which a SAR system views a given target. The HMM is trained on computed data, using SAR imagery synthesized via a validated physical-optics solution. The performance of the HMM is demonstrated by performing testing on measured UWB SAR data for many surface and shallow UXO buried in soil in the vicinity of naturally occurring clutter.

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.

Scattering from complex bodies using a combined direct and iterative technique

An iterative technique is developed for frequency-domain plane wave scattering from electrically large composite bodies. An electric field integral equation (EFIE) formulation is employed in which the submatrices of the moment-method matrix are uncoupled and the current on each geometrically separable region of the composite body is solved independently using a direct method. The currents on the various subcomponents of the body are then recalculated within an outer iterative loop. The technique is applied to the case of a multiwavelength body of revolution (BOR) with two flat-plate attachments. This composite body iterative technique is shown to preserve the simplicity and attractiveness of an isolated BOR while maintaining current continuity across the structure without the use of additional junction currents. This new formulation also allows simple suppression of interior resonance effects normally associated with large closed conducting bodies.

Multilevel fast multipole algorithm for general dielectric targets in the presence of a lossy half‐space

The multilevel fast multipole algorithm (MLFMA) is extended to the problem of an arbitrarily shaped dielectric target in the presence of a lossy, dispersive half-space. The near MLFMA terms are treated rigorously, via a complex-image-technique-based evaluation of the Sommerfeld integrals inherent to the half-space Greens function. The Greens function components for the far MLFMA terms are evaluated approximately, but accurately, via an asymptotic analysis. In this paper, we detail the scattering formulation and perform a comparison of MLFMA-generated results with those from other, simpler (and less general) models.

Quantitative Image Recovery From Measured Blind Backscattered Data Using a Globally Convergent Inverse Method

The goal of this paper is to introduce the application of a globally convergent inverse scattering algorithm to estimate dielectric constants of targets using time-resolved backscattering data collected by a U.S. Army Research Laboratory forward-looking radar. The processing of the data was conducted blind, i.e., without any prior knowledge of the targets. The problem is solved by formulating the scattering problem as a coefficient inverse problem for a hyperbolic partial differential equation. The main new feature of this algorithm is its rigorously established global convergence property. Calculated values of dielectric constants are in a good agreement with material properties, which were revealed a posteriori.

Radar Signature Prediction for Sensing-Through-the-Wall by Xpatch and AFDTD - Part II

This paper presents computer simulations of Sensing-Through-the-Wall (STTW) radar for room imaging applications. The main purpose of our investigation is to validate the radar signature prediction codes used in this type of analysis, namely Xpatch and the Finite-Difference Time-Domain (FDTD). Based on the electromagnetic simulation results, we build synthetic aperture radar (SAR) images of a complex room containing humans and furniture objects, for various look angles and polarizations. We compare the images obtained by the two modeling methods, demonstrating good accuracy for this type of application.