A new compressive-sensing-inspired approach is proposed to the detection of faulty radiators in planar antenna arrays from a reduced set of phaseless far-field measurements. In order to deal with whatever kind of arrays, the problem is cast as the recovery of the aperture-field distribution, and two new convex-programming solution procedures are introduced. The first one relies on the improvement of the Total Variation norm technique, while the second one exploits a new aperture field expansion, which allows drastically reducing the number of unknowns of the problem. A wide set of numerical experiments involving benchmark scenarios, as well as full-wave data relative to a realistic antenna, is provided in support of the given theory.

A new approach to the design of Graded Artificial Material (GAM)-based devices is proposed by exploiting the inverse scattering framework as a synthesis tool. The introduced general methodology can be applied to arbitrary far-field specifications, thus allowing the design of non-canonical devices. In particular, two different strategies are developed for GAMs based on either graded refractive index (GAMR) or graded filling factor (GAMF). In both strategies, the inverse scattering problem is solved by a proper reformulation of the Contrast Source Inversion method, wherein a proper rescaling of the amplitude of the primary sources is also used. In particular, in the first strategy, the GAMF is obtained by exploiting homogenization theories. In the second strategy, the GAMR is synthesized by exploiting a suitable representation basis for the unknown contrast function, and, then, simple analytical formulas are used to determine the corresponding GAMF. The proposed approach is assessed through the synthesis of an antenna generating a Σ/Δ reconfigurable pattern.

The orthogonality sampling method is a recently introduced qualitative inverse scattering approach for the estimation of the morphological properties of unknown targets. Both the simplicity of implementation and the applicability to various measurement configurations make this method very effective. In this paper, a general physical understanding of this otherwise ‘pure mathematical’ method is given for the first time. Such an interpretation is derived from the relationship between the currents induced in the investigated scenario and the so-called reduced scattered field, which is the core of the orthogonality sampling indicator function. Interestingly, the nature of such a relationship implies that the reduced scattered field can be related to the radiating component of the induced currents. A direct consequence of such a result is that the orthogonality sampling method is capable of imaging discontinuities within the unknown targets and hence identify regions with different electromagnetic properties. This possibility represents a unique feature among qualitative inverse scattering methods, as these latter have been introduced as tools to image just the external shape of the unknown targets. The new interpretation as well as the above distinctive capability of the orthogonality sampling method are proved with examples on both simulated and experimental data.

A new approach for determining the complex scalar field radiated by a finite-dimensional source starting from its modulus is proposed and assessed. First, by introducing a suitable relaxation, we show that the original problem can be conveniently tackled in terms of a finite number of different Convex Programming problems. Then, an effective procedure for dealing with a small number of hierarchically-ordered optimizations is introduced and discussed. Numerical experiments, including consideration of an actual radiating source and of noisy data, are provided with reference to the canonical case of far-field data and array antennas.

We present a new approach to the problem of detecting element failures in any kind of array antenna. The proposed method requires only phaseless information on the generated field and reduces as much as possible the number of needed measurements by exploiting the Compressed Sensing (CS) theory. The solution procedure works regardless of whether the probes are located in the near-field or far-field region of the antenna under test, and it is the first and only CS-based technique able to perform the diagnostics by exploiting only phaseless measurements taken exclusively in the near-field zone. It also results simple and fast as it requires a single measurement surface and reduces, in most practical instances, to the solution of a convex programming problem. The given theory is supported by very many numerical experiments involving full-wave electromagnetic simulations of realistic arrays and considering both scalar and vector fields with different types of scanning surfaces and different noise levels. Both ON-OFF and phase faults are dealt with. An experimental validation on a fabricated array is also presented.

We introduce a novel approach for the mask-constrained power synthesis of 1-D fields enabling near-field shaping according to arbitrary masks. This method presents an innovative framework based on the spectral factorization technique and a warping strategy, allowing for an accurate representation of the near field as a minimally redundant bandlimited function. This provides valuable theoretical tools to effectively solve the problem. In fact, the synthesis is formulated as a linear programming problem followed by a polynomial factorization. Additionally, the approach allows for the a-priori identification of the minimum size of the source required to fulfill a given near-field intensity mask.