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Author

Salvatore Caorsi

Bio: Salvatore Caorsi is an academic researcher from University of Pavia. The author has contributed to research in topics: Microwave imaging & Inverse scattering problem. The author has an hindex of 36, co-authored 201 publications receiving 3630 citations. Previous affiliations of Salvatore Caorsi include University of Genoa & University of Trento.


Papers
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Journal ArticleDOI
TL;DR: 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 and 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.
Abstract: 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.

156 citations

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TL;DR: The optimization of difference patterns of monopulse antennas is considered and the cost function is based on constraints on the side-lobe levels, which is efficiently solved by a differential evolution algorithm.
Abstract: 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.

146 citations

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TL;DR: In this article, the problem of the localization, shaping, and dielectric permittivity reconstruction of live targets is addressed by means of an iterative multiscaling procedure until stationary reconstructions are achieved.
Abstract: In this paper, the problem of the localization, shaping, and dielectric permittivity reconstruction of dielectric targets is addressed. The scatterers under test are inhomogeneous cylinders of arbitrary cross sections probed by a set of incident electromagnetic fields of TM type. The scattered field data are processed in order to locate and roughly recover the objects' shapes. The scatterers under test are then reconstructed with an increasing accuracy by means of an iterative multiscaling procedure until stationary reconstructions are achieved. The proposed method is presented jointly with a modified conjugate-gradient inversion procedure in order to minimize the rising cost function. However, this methodology is independent from the minimization algorithm, and other and more efficient algorithms can be used. In order to assess the effectiveness of the iterative multiscaling method, the results of several test cases (with and without noise) are presented and discussed in more detail.

137 citations

Journal ArticleDOI
TL;DR: It is proved that the convergence of an approximation is unaffected by the presence of different materials filling the cavity resonator, and 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.
Abstract: 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.

132 citations

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TL;DR: In this paper, an approach for the optimization of the beam pattern produced by massively thinned arrays is presented, which combines the most attractive features of a genetic algorithm and those of a combinatorial technique (namely, the difference sets method).
Abstract: This paper presents an approach for the optimization of the beam pattern produced by massively thinned arrays The method, which combines the most attractive features of a genetic algorithm and those of a combinatorial technique (namely, the difference sets method), is aimed at synthesizing massively thinned antenna arrays in order to suitably reduce the peak sidelobe level Selected numerical results are presented in order to assess the effectiveness and reliability of the proposed approach

131 citations


Cited by
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Journal ArticleDOI
TL;DR: A detailed review of the basic concepts of DE and a survey of its major variants, its application to multiobjective, constrained, large scale, and uncertain optimization problems, and the theoretical studies conducted on DE so far are presented.
Abstract: Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE operates through similar computational steps as employed by a standard evolutionary algorithm (EA). However, unlike traditional EAs, the DE-variants perturb the current-generation population members with the scaled differences of randomly selected and distinct population members. Therefore, no separate probability distribution has to be used for generating the offspring. Since its inception in 1995, DE has drawn the attention of many researchers all over the world resulting in a lot of variants of the basic algorithm with improved performance. This paper presents a detailed review of the basic concepts of DE and a survey of its major variants, its application to multiobjective, constrained, large scale, and uncertain optimization problems, and the theoretical studies conducted on DE so far. Also, it provides an overview of the significant engineering applications that have benefited from the powerful nature of DE.

4,321 citations

Journal ArticleDOI
TL;DR: A comprehensive review of the various techniques used for terahertz image formation can be found in this paper, as well as numerous examples which illustrate the many exciting potential uses for these emerging technologies.
Abstract: Within the last several years, the field of terahertz science and technology has changed dramatically. Many new advances in the technology for generation, manipulation, and detection of terahertz radiation have revolutionized the field. Much of this interest has been inspired by the promise of valuable new applications for terahertz imaging and sensing. Among a long list of proposed uses, one finds compelling needs such as security screening and quality control, as well as whimsical notions such as counting the almonds in a bar of chocolate. This list has grown in parallel with the development of new technologies and new paradigms for imaging and sensing. Many of these proposed applications exploit the unique capabilities of terahertz radiation to penetrate common packaging materials and provide spectroscopic information about the materials within. Several of the techniques used for terahertz imaging have been borrowed from other, more well established fields such as x-ray computed tomography and synthetic aperture radar. Others have been developed exclusively for the terahertz field, and have no analogies in other portions of the spectrum. This review provides a comprehensive description of the various techniques which have been employed for terahertz image formation, as well as discussing numerous examples which illustrate the many exciting potential uses for these emerging technologies.

962 citations

Journal ArticleDOI
TL;DR: In this paper, finite element Galerkin schemes for a number of linear model problems in electromagnetism were discussed, and the finite element schemes were introduced as discrete differential forms, matching the coordinate-independent statement of Maxwell's equations in the calculus of differential forms.
Abstract: This article discusses finite element Galerkin schemes for a number of linear model problems in electromagnetism. The finite element schemes are introduced as discrete differential forms, matching the coordinate-independent statement of Maxwell's equations in the calculus of differential forms. The asymptotic convergence of discrete solutions is investigated theoretically. As discrete differential forms represent a genuine generalization of conventional Lagrangian finite elements, the analysis is based upon a judicious adaptation of established techniques in the theory of finite elements. Risks and difficulties haunting finite element schemes that do not fit the framework of discrete differential forms are highlighted.

890 citations

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TL;DR: The feasibility of detecting and localizing small (<1 cm) tumors in three dimensions with numerical models of two system configurations involving synthetic cylindrical and planar antenna arrays with image formation algorithms developed to enhance tumor responses and reduce early- and late-time clutter are demonstrated.
Abstract: The physical basis for breast tumor detection with microwave imaging is the contrast in dielectric properties of normal and malignant breast tissues. Confocal microwave imaging involves illuminating the breast with an ultra-wideband pulse from a number of antenna locations, then synthetically focusing reflections from the breast. The detection of malignant tumors is achieved by the coherent addition of returns from these strongly scattering objects. In this paper, we demonstrate the feasibility of detecting and localizing small (<1 cm) tumors in three dimensions with numerical models of two system configurations involving synthetic cylindrical and planar antenna arrays. Image formation algorithms are developed to enhance tumor responses and reduce early- and late-time clutter. The early-time clutter consists of the incident pulse and reflections from the skin, while the late-time clutter is primarily due to the heterogeneity of breast tissue. Successful detection of 6-mm-diameter spherical tumors is achieved with both planar and cylindrical systems, and similar performance measures are obtained. The influences of the synthetic array size and position relative to the tumor are also explored.

884 citations