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Quantitative inversion of GPR data opens the door to precise characterization of underground environments. However, in order to make the inverse scattering problem solution easier from a computational viewpoint, simplifying assumptions are often applied, i.e., two-dimensional approximations or the consideration of idealized field probes and electromagnetic sources. These assumptions usually produce modeling errors, which can degrade the dielectric reconstruction results considerably. In this article, a processing step based on long short-term memory cells is proposed for the first time to correct the modeling error in a multiantenna GPR setting. In particular, time-domain GPR data are fed into a neural network trained with couples of finite-difference time-domain simulations, where a set of sample targets are simulated in both realistic and idealized configurations. Once trained, the neural network outputs an approximation of multiantenna GPR data as they are collected by an ideal two-dimensional measurement setup. The inversion of the processed data is then accomplished by means of a regularizing Newton-based nonlinear scheme with variable exponent Lebesgue space formulation. A numerical study has been conducted to assess the capabilities of the proposed inversion methodology. The results indicate the possibility of effectively compensating for modeling error in the considered test cases. [ABSTRACT FROM AUTHOR]

A microwave characterization technique to inspect subsurface scenarios is proposed and numerically assessed in this paper. The approach is based on a combination of finite element electromagnetic modeling and an inversion procedure in Lebesgue spaces with variable exponents. The former allows for description of the measurement system and subsurface scenario with high accuracy, while the latter exploits the adaptive definition of exponent function to achieve improved results in the regularized solution of the inverse scattering problem. The method has been assessed with numerical simulations regarding two-layered environments with both planar and non-planar air–soil interfaces. The results show the capabilities of the method of detecting buried objects in different operative conditions. [ABSTRACT FROM AUTHOR]

In this communication, a semianalytical solution for the computation of the 2-D Green’s function for a cylindrical perfect electric conducting (PEC) enclosure containing an arbitrary number of confocal elliptic dielectric layers is provided. The approach relies on an expansion of the Green’s function into Mathieu functions, whose coefficients are found in an efficient way through a recursive procedure. The effectiveness of the technique is evaluated by comparisons with analytical formulas and against the results provided by independent numerical solvers. Moreover, the applicability of the solution to forward scattering problems using integral formulations is also assessed. In all the considered cases, the developed approach has been found to provide accurate results. [ABSTRACT FROM AUTHOR]

The Fourier transform (FT) of the electric field (EF) radiated by a lightning return stroke is shown to include a distributional term at zero frequency, which prevents numerical algorithms, such as fast FT, from working properly. Inspired by the finite duration of any field measurement in real applications, we introduce a time-windowing strategy, whereby the integration time-interval of the FT becomes bounded. As a result, the distributional term is removed from the FT, whereas the functional part of the FT is modified throughout the whole range of frequencies, in such a way that a good performance of the numerical algorithms can be restored. The dependence of the modified spectra of the EFs on the length of the time window is also investigated and three numerical experiments with different channel-base currents are performed to validate the whole resulting framework. [ABSTRACT FROM AUTHOR]

A hybrid approach is proposed to inspect three-dimensional homogeneous dielectric scatterers by using microwaves. Namely, the considered method consists in two steps: first, the supports of the scatterers are retrieved by the linear sampling method; then the permittivities of the targets are estimated by an ant colony optimization algorithm. The described strategy combines the efficiency of the linear sampling method with the global optimization capabilities of the stochastic procedure. Numerical results assess the capabilities of the approach also in the presence of noise. Index Terms--Ant colony optimization (ACO), inverse scattering, linear sampling method (LSM), stochastic methods.

A new approach to noninvasive inspection of dielectric targets at microwave frequencies is proposed. Cylindrical dielectric objects are reconstructed under the second-order Born approximation. A multi-illumination configuration is considered. The continuous model is discretized by the moment method and an efficient inexact-Newton method is applied. The dielectric profile is iteratively reconstructed starting from the measured scattered data, which are related to the unknown target through the inverse scattering equations written in a variational setting. Several numerical results are reported, which are aimed at assessing the capabilities of the approach in dealing with the nonlinear ill-posed inverse problem associated to the short-range microwave imaging. Single, multilayer, and separate cylinders are reconstructed in noiseless and noisy environments. Index Terms--Dielectrics, imaging, inverse scattering, iterative regularization, Newton methods.

In this paper, the use of a smart antenna system for the estimation of the directions of arrival (DOAs) of multiple waves is considered. An efficient method based on the support vector regression is proposed, in which the mapping among the outputs of the array and the DOAs of unknown plane waves is approximated by means of a family of support vector machines. Several numerical results are provided for the validation of the proposed approach, considering multiple impinging waves both in noiseless and noisy environments. Index Terms--Antenna arrays, direction of arrival (DOA) estimation, regression, support vector machines.

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. Index Terms--Array antennas, evolutionary algorithm, monopulse antennas, sum and difference patterns.

Phaseless data are used to evaluate the application of an electromagnetic inverse-scattering-based procedure for the detection of cylindrical inhomogeneities, which are schematized as multilayer infinite dielectric cylinders with elliptic cross sections. The electromagnetic inverse problem is recast as a global optimization problem and iteratively solved by an efficient memetic algorithm, which combines deterministic and stochastic concepts. Moreover, a recursive analytical procedure is used for the forward-scattering computation. The possibility of localizing and reconstructing the scatterers by using phaseless input data, which would greatly simplify the design of the imaging apparatus, is evaluated both with reference to synthetically produced data and by means of experimental data obtained by a microwave tomograph. Index Terms--Electromagnetic imaging, elliptic cylinders, genetic algorithms, inverse scattering.

The application of a global optimization procedure to the detection of buried inhomogeneities is studied in the present paper. The object inhomogeneities are schematized as multilayer infinite dielectric cylinders with elliptic cross sections. An efficient recursive analytical procedure is used for the forward scattering computation, A functional is constructed in which the field is expressed in series solution of Mathieu functions. Starting by the input scattered data, the iterative minimization of the functional is performed by a new optimization method called memetic algorithm. Index Terms--Electromagnetic imaging, elliptic cylinders, evolutionary algorithms.

To date, tumors, the second cause of death worldwide, are a modern medicine plight. The development of rapid, cost-effective and reliable prevention and diagnostics tools is mandatory to support clinicians and ensure patients' adequate intervention. Pituitary tumors are a class of neoplasm, which calls for suitable and ad hoc diagnostic tools. Recently, microwaves have gained interest as a non-ionizing, non-invasive valuable diagnostic approach for identifying pathologic tissues according to their dielectric properties. This work deals with the preliminary investigation of the feasibility of using microwaves to diagnose pituitary tumors. In particular, it focuses on benign tumors of the adenohypophysis, e.g., the pituitary adenomas. It is assumed to access the region of interest of the pituitary region by following a trans-sphenoidal approach. The problem was modeled by developing an equivalent transmission line model of the multi-layered, lossy tissues (front bone of sphenoid sinuses, air in the sinuses, posterior bone of sphenoid sinuses, the pituitary gland and the tumor). The forward problem was developed to investigate the transmission coefficient for identifying the most favorable propagation conditions. Then, it was analyzed if, by the solution of an inverse problem, it is possible to reconstruct the permittivity and electrical conductivity profiles and identify the tumor presence. The results are promising since a maximum reconstruction error of 8% is found, in the worst case, thus paving the way for the use of microwaves for the diagnosis of pituitary tumors. [ABSTRACT FROM AUTHOR]

In this article, a new microwave-radar-based technique for short-range detection and classification of multiple human and vehicle targets crossing a monitored area is proposed. This approach, which can find applications in both security and infrastructure surveillance, relies upon the processing of the scattered-field data acquired by low-cost off-the-shelf components, i.e., a 24 GHz frequency-modulated continuous wave (FMCW) radar module and a Raspberry Pi mini-PC. The developed method is based on an ad hoc processing chain to accomplish the automatic target recognition (ATR) task, which consists of blocks performing clutter and leakage removal with an infinite impulse response (IIR) filter, clustering with a density-based spatial clustering of applications with noise (DBSCAN) approach, tracking using a Benedict-Bordner $\alpha $ - $\beta $ filter, features extraction, and finally classification of targets by means of a $k$ -nearest neighbor ($k$ -NN) algorithm. The approach is validated in real experimental scenarios, showing its capabilities in correctly detecting multiple targets belonging to different classes (i.e., pedestrians, cars, motorcycles, and trucks). [ABSTRACT FROM AUTHOR]

An iterative multiscaling approach for solving the electromagnetic inverse scattering problem related to the imaging of shallow subsurface targets with the ground-penetrating radar (GPR) is proposed. The approach combines the zooming properties of the multiscaling technique with the reconstruction capabilities of an Inexact-Newton (IN) method developed in $L^{p}$ spaces. It is based on multifrequency processing that allows one to face the ill-posedness of the inverse scattering problem by exploiting the regularization properties of a truncated Landweber (LW) method. Experimental data, extracted from radargrams obtained by the GPR in a real situation, are used for validation. The reconstruction results are also compared with those from competitive alternatives, such as a standard IN method or a state-of-the-art multifrequency Conjugate Gradient (CG)-based approach. [ABSTRACT FROM AUTHOR]