Nicola Anselmi

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An innovative strategy for the robust design of linear antenna arrays is presented. Being the array elements characterised by tolerance errors, the synthesis is aimed at determining the intervals of values fitting the user-defined mask constraints on the radiated power pattern. With reference to the upper and lower bounds of the power pattern analytically(More)
The inspection of 2-D scatterers buried in a lossy half-space from field measurements is formulated within the framework of the second-order Born approximation (SOBA) of the inverse scattering problem. An iterative multi-scaling approach (IMSA) is combined with a two-step inexact-Newton (IN) algorithm to solve the arising problem. A set of preliminary(More)
The analysis of the tolerance effects on the radiated power pattern caused by the fabrication errors in the printing of the microstrip patches of reflectarrays is addressed through a method based on the Interval Analysis and the arithmetic of intervals. The dimensions of the microstrip patches are defined as intervals of values including the tolerance(More)
An innovative method for the synthesis of robust beam-forming weights of linear antenna arrays is presented in this work. Starting from user-defined mask power constraints, the configuration of the amplitude weights is optimized by means of a hybrid tool integrating the Interval Analysis (IA) and the Particle Swarm Optimization (PSO) in order to maximize(More)
A task-oriented <italic>multiscale</italic> material synthesis problem is addressed through an instance of the system-by-design (SbD) paradigm. More specifically, wide-angle impedance matching (WAIM) layers based on printed metasurfaces are designed to enhance the radiation efficiency of planar phased arrays. Toward this end, a task-oriented formulation is(More)
The sensitivity to both calibration errors and mutual coupling effects of the power pattern radiated by a linear array is addressed. Starting from the knowledge of the nominal excitations of the array elements and the maximum uncertainty on their amplitudes, the bounds of the pattern deviations from the ideal one are analytically derived by exploiting the(More)
This paper presents an innovative microwave imaging technique for detecting defects in dielectric or conductive media developed through the Bayesian Compressive Sensing theory. Thanks to the a-priori knowledge of the medium unaffected by defects, the inversion problem is formulated as the estimation of the sparse differential equivalent currents within the(More)
An Alphabet Compressive Sensing (CS) approach is proposed in this paper for the retrieval of arbitrarily-shaped targets when no a-priori information on the class of scatterers at hand is available. The approach is based on the combination of (i) a fast CS retrieval methodology that is employed to invert the field data assuming several different candidate(More)
The analysis of the effects on the power pattern radiated by reflector antennas in presence of localized defects (also called bumps) of the parabolic surface is addressed by means of an innovative analytic strategy. The bump depths are supposed unknown or estimated with a given tolerance such that their deviations from the nominal surface can be expressed(More)