Lorenza Tenuti

An SbD-QCTO Approach to the Synthesis of Isotropic Metamaterial Lenses

Within the transformation electromagnetics (TE) framework, an innovative approach, based on the System-by-Design paradigm, is proposed for the synthesis of isotropic nonmagnetic metamaterial lenses. Selected numerical results, concerned with an application of the SbD-QCTO approach, are reported to give some insights on its advantages and current limitations in terms of computational efficiency, effectiveness, and flexibility.

Minkowski Sum Method for Planar Arrays Sensitivity Analysis With Uncertain-But-Bounded Excitation Tolerances

The sensitivity of the power pattern generated by a planar array to both amplitude and phase excitation errors is addressed. Under the hypothesis of uncertain, but bounded, tolerances on the element excitations, an innovative approach based on the integration of the interval analysis and the Minkowski sum is proposed to predict tight, reliable, and inclusive pattern bounds. Representative numerical results are reported and discussed to point out the potentialities and the effectiveness of the proposed approach also in comparison with the state-of-the-art interval-based methods.

Imaging complex targets through alphabet-based compressive sensing

Imaging techniques exploiting sparseness-regularized formulations emerged in the last few years as powerful and effective retrieval methods in several heterogeneous scenarios [1] including structural monitoring, non-destructive testing and evaluation, ground penetrating radar imaging, and biomedical diagnosis [2-8]. The success of the this class of algorithms, which are often collectively indicated as Compressive Sensing (CS) [9], is motivated by several concurring factors, including their accuracy, robustness, numerical efficiency, capability to handle several different contexts (e.g., including transverse-magnetic [2] and transverse-electric problems [3], single-/multi-frequency data [2, 4], isotropic/anisotropic media [1]) in a seamless way, and the availability of efficient implementations of many different solvers [1]. On the other hand, CS techniques are not general-purpose imaging algorithms. Their application requires the problem at hand to comply with some fundamental assumptions [1], including the fact that the unknown (e.g., the contrast [8] or equivalent currents [9]) is sparse in the employed basis. Early applications of CS methods, which used simple pixel-bases to expand the unknowns, addressed only those scenarios were the object is composed by few isolated pixels [2]. Nevertheless, it is well known that sparsity is not an absolute concept, but it is always in relation with the representation basis [1]. The use of different expansion bases [10] has been then proposed to enable more complex profiles to be imaged [7]. Unfortunately, such techniques always assume that some knowledge on the target profile is available, so that this a-priori information can be exploited to define the most suitable expansion basis to be adopted [7]. A different perspective is considered in this paper to enable the application of CS methodologies when no prior information on the class of targets under investigation is available. More specifically, a large alphabet of candidate bases is generated off-line, and for each basis a candidate reconstructions are carried out in parallel “online” by the CS retrieval tool. The retrieved profiles are then compared, and a sparsity-based criterion is adopted in turns to select the most reliable reconstruction (among those obtained by the different bases). Preliminary numerical experiments will be shown to assess the accuracy and numerical efficiency of the proposed imaging methodology.

A comparative assessment of information-exploitation techniques for GPR data inversion

The inversion of Ground Penetrating Radar (GPR) data requires the development of suitable information-exploitation techniques that are able to extract as much as possible information on the unknown targets from the available measurements. An innovative singlefrequency (SF) inversion technique based on a deterministic conjugate-gradient (CG) minimization and the iterative multi-scaling approach (IMSA) is described. It is then shown how to improve the performances of the SF-IMSA-CG method by the introduction of an external frequency hopping (FH) iterative loop. On the one hand, the proposed FH-IMSA-CG method allows to exploit the intrinsic frequency diversity of wideband GPR measurements thanks to the FH strategy. On the other hand, the IMSA approach guarantees a significant reduction of the problem unknowns, providing an increased resolution within the identified regions of interest (RoIs). A numerical comparison shows the advantages of the FH-IMSA-CG over its single-frequency version. Moreover, the benefits of integrating the IMSA within the FH are verified by directly comparing the FH-IMSA-CG with its single-resolution (BARE) version (FH-BARE-CG).

Metamaterial-enhanced arrays by innovative QCTO approaches

Quasi Conformal Transformation Optics (QCTO) is applied in innovative antenna array enhancement applications. The QCTO is implemented numerically. Examples provided include miniaturization of a linear array using isotropic metamaterial lens and transformation of an arbitrary shaped conformal array to a well known (for example circular) array. A full-wave electromagnetic simulation is used to validate the approach.

Optimization-based design of innovative grating-lobe free radar UWB architectures

An innovative approach for reducing grating lobes appearing when the inter-element spacing of an UWB linear array is greater than half-wavelength is presented. The main innovation of the proposed new design methodology is related to the fact that the positions of the array elements are left unchanged in the direction of the axis of the array (thus not affecting the gain of the pattern), while they are optimized along broadside direction. Selected numerical results validate the proposed methodology.

Synthesis of next generation reflectarrays

In this work, the problem of efficiently and accurately predicting the scattering coefficient matrices of complex reflectarrays elements is addressed. The solution proposed does not resort to numerically expensive full-wave simulators. On the contrary, it exploits an advanced Learning-by-Example technique which predicts the matrix which describes the behaviour of the wave reflected by the unit cell. Some preliminary results show the accuracy and the saving time of the proposed methodology in comparison with standard approaches.

CS-based computational imaging at microwave frequencies

A review of the features, potentialities, and applications of Compressive Sensing (CS) methodologies in the solution of computational imaging problems is presented in this work. Towards this end, the most popular formulations for the solution of CS imaging problems at microwave frequencies are illustrated, and the advantages/limitations of current techniques developed in this framework are discussed, along with the recent advances in the field. Some numerical examples are presented to show the current trends and envisaged developments of CS-based computational imaging strategies.

A System-by-Design approach for the synthesis of multi-layer mantle cloaks

The problem of designing a multi-layer mantle cloak suitable for large dielectric cylinders is addressed through an innovative System-by-Design-Scattering Cancellation (SbD-SC) procedure. More in detail, the minimization of the overall Scattering Cross Section (SCS) is obtained by adjusting the multi-layer cover parameters (i.e., surface impedances and radii) so that both the fundamental and the higher order scattering modes are canceled. The arising design problem is solved through an instance of the SbD paradigm, which is adopted to effectively and efficiently explore the solution space. The features of the proposed SbD-SC technique are illustrated through a preliminary numerical example.

Complex radome design through the Systems-by-Design approach

An effective approach for the design and optimization of complex radome structures based on the System-by-Design (SbD) paradigm is presented. The proposed approach is based on the integration of suitable synthesis and analysis blocks exploiting surrogate models which enable the optimization of the radome parameters and structure. The surrogate model is used in this case to predict the values of the cost function in the optimization step. A representative result is reported to show the potentialities of the SbD-based design methodology.