Salvatore Caorsi

A computational technique based on a real-coded genetic algorithm for microwave imaging purposes

A computational approach based on a genetic algorithm is proposed for the solution of a nonlinear inverse scattering problem for short-range microwave imaging applications. Starting from an integral-equation formulation, the aim is to derive locations, shapes, and distributions of the dielectric parameters of cylindrical scatterers. Simultaneously, the approach also provides the distributions of the internal total electric field. After discretization, the problem is recast as a nonlinear optimization problem. The paper exploits the application of a real-coded genetic algorithm in order to minimize a suitable functional. The reconstruction of strong scatterers with a resolution beyond the Rayleigh criterion is shown, and computational aspects are discussed. Comparisons with results obtained by using approximated formulations and a binary-coded genetic algorithm are also provided. Finally, a hybrid version of the approach (based on the combined strategy of the genetic algorithm and a conjugate gradient method) is presented and preliminarily tested.

Optimization of the difference patterns for monopulse antennas by a hybrid real/integer-coded differential evolution method

The optimization of difference patterns of monopulse antennas is considered. The synthesis problem is recast as an optimization problem by defining a suitable cost function. In particular, in this paper, the cost function is based on constraints on the side-lobe levels. A subarray configuration is adopted and the excitations of the difference pattern are approximately determined. The optimization problem is efficiently solved by a differential evolution algorithm, which is able to contemporarily handle real and integer unknowns. Numerical results are reported concerning classical array configurations previously considered in the literature.

On the Convergence of Galerkin Finite Element Approximations of Electromagnetic Eigenproblems

The convergence of Galerkin finite element approximations of electromagnetic eigenproblems modelling cavity resonators is studied. Since the operator involved is noncompact, the first part of the analysis is carried out in terms of the specific definition of convergence that is known to be appropriate for this case. Then, a slightly stronger definition of convergence is proposed, which is tuned to the features a practitioner of the numerical simulation of electromagnetic devices requires for a good computational model of a resonant cavity. For both definitions, necessary and sufficient conditions are introduced and discussed. Moreover, it is proved that the convergence of an approximation in the stronger sense is unaffected by the presence of different materials filling the cavity resonator. Exploiting this basic feature of the newly defined convergence, the previously developed theory is applied to generalize the convergence proof for the lowest order edge element approximations to the case of anisotropic, inhomogeneous and discontinuous material properties. Results clarifying the relationships among the various conditions occurring in our analysis and examples showing what may happen when not all the conditions for convergence hold true are also reported and contribute to a clear picture about the origin and the behavior of spurious modes.

Two-dimensional microwave imaging by a numerical inverse scattering solution

A numerical approach that aims to detect, by means of interrogating microwaves, the locations and the dielectric permittivities of unknown inhomogeneous dielectric cylindrical objects of arbitrary cross sections that might be present inside a fixed area of interest is proposed. An illumination is assumed with the electric field vector polarized along the cylindrical axis. The two-dimensional Lippman-Schwinger integral equation of electromagnetic scattering is transformed into matrix form by the moment method. The system obtained is solved by using a pseudoinversion algorithm to overcome ill-conditioning problems. The first-order Born approximation is also applied when the dielectric inhomogeneities are weakly scattering. Computer simulations have been performed by means of a numerical program. Results show the capabilities and limitations of the proposed approach. >

A microwave inverse scattering techniques for image reconstruction based on a genetic algorithm

The problem of reconstructing locations, shapes, and dielectric permittivity distributions of two-dimensional dielectric objects from measurements of the scattered electric field is addressed. A numerical approach is proposed which is based on a multi-illumination multiview processing. In particular, the inverse problem is recast as a global nonlinear optimization problem, which is solved by a genetic algorithm. The final objective of the approach is the image reconstruction of highly contrasted bodies.

Detection, location, and imaging of multiple scatterers by means of the iterative multiscaling method

In this paper, a new version of the iterative multiscaling method (IMM) is proposed for reconstructing multiple scatterers in two-dimensional microwave imaging problems. This paper describes the new procedure evaluating the effectiveness of the IMM previously assessed for single object detection. Starting from inverse scattering integral equations, the problem is recast in a minimization one by defining iteratively (at each level of the scaling procedure) a suitable cost function, firstly allowing a detection of the unknown objects, successively a location of the scatterers, and finally, a quantitative reconstruction of the scenario under test. Thanks to its properties, the approach allows an effective use of the information achievable from inverse scattering data. Moreover, the adopted kind of expansion is able to deal with all possible multiresolution combinations in an easy and computationally inexpensive way. Selected numerical examples concerning dielectric, as well as dissipative objects in noisy environments or starting from experimentally acquired data are reported in order to confirm the usefulness of the introduced tool and of the effectiveness of the proposed procedure.

Electromagnetic scattering by a multilayer elliptic cylinder under transverse-magnetic illumination: series solution in terms of Mathieu functions

An exact solution to the electromagnetic scattering by a dielectric multilayer infinite cylinder of elliptic cross section is proposed. The interfaces between different media, which are assumed to be lossless and nonmagnetic, are confocal elliptic cylinders. Starting from the series expansions in terms of Mathieu functions, an efficient recursive procedure for the computation of fields and radar cross sections per unit length under a transverse-magnetic illumination is developed. The mathematical formulation is detailed and some numerical results are provided.

LINEAR ANTENNA SYNTHESIS WITH A HYBRID GENETIC ALGORITHM

An optimization problem for designing non-uniformly spaced, linear arrays is formulated and solved by means of an improved genetic algorithm (IGA) procedure. The proposed iterative method aims at array thinning and optimization of element positions and weights by minimizing the side-lobes level. Selected examples are included, which demonstrate the effectiveness and the design flexibility of the proposed method in the framework of electromagnetic synthesis of linear arrays.

Electromagnetic detection of dielectric cylinders by a neural network approach

The neural network approach is applied to the detection of cylindric objects as well as their geometric and electrical characteristics inside a given investigation domain. The electric field values scattered by the object and available at a small number of locations are fed into the network, whose output is the dielectric permittivity, and the location and radius of the cylinder. The results are evaluated using different sets of testing data, and the dependence of the various output parameters to the input are considered. The algorithm performance shows that the approach is able to solve the inverse scattering problem quickly. This may be useful for real-time remote-sensing applications.

A global optimization technique for microwave nondestructive evaluation

A global optimization technique based on a genetic algorithm is proposed for microwave nondestructive evaluation. Starting from an integral formulation of the inverse scattering problem, the detection of a flaw in a known host medium is reduced to the minimization of a suitable nonlinear functional relating the measured field to the field predicted at a given iteration. The geometrical parameters of the flaw are retrieved by using a tomographic imaging approach. Numerical results are reported concerning cracks in lossless and lossy structures. The effects of the noise on measured input data are also analyzed.