Marco Salucci

Design of a UHF RFID/GPS Fractal Antenna for Logistics Management

In this paper, a planar multi-band antenna suitable for the integration in portable terminal systems is described. The antenna operates at UHF RFID (915 MHz) and GPS-L1 (1715 MHz) frequency bands to supply chain operations and asset tracking in supply chain management. The performance of the proposed antenna is assessed through numerical and experimental tests.

GPR Prospecting Through an Inverse-Scattering Frequency-Hopping Multifocusing Approach

An innovative information-acquisition approach to 2-D ground-penetrating radar (GPR) prospecting is presented. A microwave inverse-scattering nested scheme combining a frequency hopping (FH) procedure and a multifocusing (MF) technique is proposed. On the one hand, the FH scheme effectively handles multifrequency GPR data, whereas on the other hand, MF techniques have been proven to be effective tools in reducing the occurrence of multilocal minima affecting GPR investigations. This allows the use of a local search technique based on the conjugate gradient method to iteratively solve the inverse problem at hand. Selected results are reported and analyzed to give some insights to the interested readers on the advantages and limitations of such an approach when handling synthetically generated and experimental GPR data.

Multiband fractal Zigbee/WLAN antenna for ubiquitous wireless environments

In this paper, a multiband antenna based on a perturbed Sierpinski Gasket fractal for distributed systems in ubiquitous wireless environments is presented. The antenna enables communication services within the 868/915 MHz ZigBee bands and in the 2.4 GHz WLAN frequencies. The geometrical characteristics of the radiator are determined to fit the electrical and radiation requirements through an optimization approach based on a particle swarm strategy. The prototype performances are assessed through numerical and experimental validations.

Wavelet-Based Compressive Imaging of Sparse Targets

The application of the compressive sensing (CS) paradigm to retrieve non-single-pixels contrast profiles is discussed. By exploiting a wavelet representation to model complex scatterer distributions with sparse vectors of coefficients, an efficient Bayesian CS (BCS) strategy is adopted to solve the arising inverse scattering problem. A set of representative numerical examples is presented to illustrate the advantages and the limitations of the proposed approach also with respect to comparable state-of-the-art inversion methods.

Reconfigurable Thinning for the Adaptive Control of Linear Arrays

Dealing with the adaptive nulling of the array radiation pattern, two reconfigurable thinning strategies are presented and assessed. An easily-reconfigurable and low-complexity antenna architecture is considered where a set of radio-frequency switches is exploited to either connect or disconnect the array elements for controlling the radiation pattern and generating deep nulls along the directions-of-arrival of the undesired signals. By defining through a genetic algorithm-based optimization the on/off status of the switches to maximize the signal-to-interference-plus-noise ratio at the antenna output, two different formulations are discussed. The first one does not constrain the number of active elements, while the other forces the solution to satisfy a fixed-directivity criterion also in correspondence with a time-varying interference scenario. The performances of the proposed approaches are assessed in both static and time-varying scenarios where single and multiple interfering signals impinge on the array from different angular directions.

Multifrequency Particle Swarm Optimization for Enhanced Multiresolution GPR Microwave Imaging

An innovative inverse scattering (IS) technique for the simultaneous processing of multifrequency (MF) ground-penetrating radar (GPR) measurements is proposed. The nonlinear IS problem is solved by profitably integrating a customized MF version of the particle swarm optimizer (PSO) within the iterative multiscaling approach (IMSA) to jointly exploit the reduction of the ratio between unknowns and uncorrelated data with a pervasive exploration of the multidimensional search space for minimizing the probability that the solution is trapped into local minima corresponding to false solutions of the problem at hand. Both numerical and experimental test cases are reported to assess the reliability of the MF-IMSA-PSO method toward accurate GPR tomography as well as improvements with respect to the competitive state-of-the-art inversion approaches.

Array Miniaturization Through QCTO-SI Metamaterial Radomes

The array miniaturization problem is addressed by means of a material-by-design approach. More specifically, an innovative strategy that integrates a quasi-conformal transformation optics (QCTO) technique and a source inversion method is proposed to design radome-coated arrays exhibiting the same radiation properties of wider virtual arrangements comprising more antenna elements. Toward this end, the state-of-the-art QCTO theory is generalized to account for source constraints within the synthesis process. Representative numerical examples are provided to assess the reliability, the flexibility, and the effectiveness of the proposed synthesis approach as well as the possibility to realize suboptimal radomes with simplified, but cheaper/easier, structures (e.g., structures based on tiles of isotropic dielectrics).

Advanced multi-frequency GPR data processing for non-linear deterministic imaging

Abstract In this paper, the quantitative imaging of the dielectric characteristics of unknown targets buried in a lossy half-space is performed by suitably processing wide-band ground penetrating radar (GPR) measurements. An innovative multi-frequency (MF) fully non-linear inverse scattering (IS) technique exploiting the integration of a conjugate-gradient (CG) solver within the iterative multi-scaling approach (IMSA) is proposed. Representative results from numerical test cases are presented to provide the interested readers with some indications on the effectiveness, as well as the current limitations, of the proposed approach when directly compared to a state-of-the-art frequency-hopping (FH) based method formulated in the same framework. Such a validation points out that if, on the one hand, the proposed MF strategy is computationally more efficient than the FH one, on the other hand, it turns out to be less reliable and accurate in several situations.

Synthesis of Modular Contiguously Clustered Linear Arrays Through a Sparseness-Regularized Solver

An innovative methodology for the design of modular and contiguously-clustered linear arrays is proposed. The approach formulates the subarraying problem as a pattern matching one in which elementary modules taken from a user-defined dictionary are combined to synthesize the final antenna layout. By recasting such a synthesis problem within the compressive sensing framework, an efficient solver is used to determine the array architecture starting from the a priori specification of the features (e.g., the length) of the admissible subarrays. A set of representative numerical experiments is discussed to assess the advantages and drawbacks of the proposed algorithm also in comparison with some state-of-the-art methods.

Real-Time NDT-NDE Through an Innovative Adaptive Partial Least Squares SVR Inversion Approach

The real-time retrieval of the characteristics of a defect with eddy current testing in a nondestructive testing and evaluation framework is addressed. An innovative statistical learning approach is developed to deal with the inversion problem at hand in a computationally efficient way. More in detail, a feature extraction technique based on partial least squares (PLS) is profitably combined with a customized output space filling (OSF) adaptive sampling scheme for generating optimal training databases, while accurate and robust reconstructions are performed with a support vector regression (SVR) algorithm. A selected set of numerical and experimental results is reported to assess the effectiveness as well as the efficiency of the proposed PLS-OSF/SVR approach.