We introduce a fast algorithm for computing volume potentials -that is, the convolution of a translation invariant, free-space Green's function with a compactly supported source distribution defined on a uniform grid. The algorithm relies on regularizing the Fourier transform of the Green's function by cutting off the interaction in physical space beyond the domain of interest. This permits the straightforward application of trapezoidal quadrature and the standard FFT, with superalgebraic convergence for smooth data. Moreover, the method can be interpreted as employing a Nystrom discretization of the corresponding integral operator, with matrix entries which can be obtained explicitly and rapidly. This is of use in the design of preconditioners or fast direct solvers for a variety of volume integral equations. The method proposed permits the computation of any derivative of the potential, at the cost of an additional FFT.

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We present a new formulation for the problem of electromagnetic scattering from perfect electric conductors. While our representation for the electric and magnetic fields is based on the standard vector and scalar potentials A; in the Lorenz gauge, we establish boundary conditions on the potentials themselves rather than on the field quantities. This permits the development of a wellconditioned second-kind Fredholm integral equation that has no spurious resonances, avoids low-frequency breakdown, and is insensitive to the genus of the scatterer. The equations for the vector and scalar potentials are decoupled. That is, the unknown scalar potential defining the scattered field, scat , is determined entirely by the incident scalar potential inc . Likewise, the unknown vector potential defining the scattered field, A scat , is determined entirely by the incident vector potential A inc . This decoupled formulation is valid not only in the static limit but for arbitrary ! 0.

Abstract-A microwave tomographic scanner for biomedical applications is presented. The scanner consists of a 64 element circular array with a useful diameter of 20 cm. Electronically scanning the transmitting and receiving antennas allows mnltiview measurements with no mechanical movement. Imaging parameters are appropriate for medical use: a spatial resolution of 7 mm and a contrast resolution of 1% for a measurement time of 3 s. Measurements on tissue-simulating phantoms and volunteers, together with numerical simulations, are presented to assess the system for absolute imaging of tissue distribution and for differential imaging of physiological, pathological, and induced changes in tissues.

his paper presents a new and original approach to computing T the high-frequency radar cross section (RCS) of complex radar targets in real time, using a 3D graphics workstation. The target (typically, an aircraft) is modeled with the I-DEAS solid-modeling software, using a parametric-surface approach. The high-frequency RCS is obtained through Physical Optics (PO), Method of Equivalent Currents (MEC), Physical Theory of Diffraction (PTD), and Impedance Boundary Condition (IBC) techniques.This method is based on a new and original implementation of high-frequency techniques, which we have called "Graphical Electromagnetic Computing (GRECO)." A graphical-processing approach to an image of the target on the workstation screen is used to identify the surfaces of the target, visible from the radar viewpoint, and to obtain the unit normal at each point of these surfaces. High-frequency approximations to RCS prediction are then easily computed from the knowledge of the unit normal at the illuminated surfaces of the target.The image of the target on the workstation screen, to be processed by GRECO, is obtained, in real time, from an I-DEAS geometric model, using the 3D graphics hardware accelerator of the workstation. Therefore, the CPU time for the RCS prediction is spent only on the electromagnetic part of the computation, while the more time-consuming geometric-model manipulations are left to the grqphics hardware. This hybrid, graphic-electromagnetic computing (GRECO) results in real-time RCS prediction for complex radar targets.