Antonia Rita Lagana

ON THE OPTIMAL SYNTHESIS OF RING SYMMETRIC SHAPED PATTERNS BY MEANS OF UNIFORMLY SPACED PLANAR ARRAYS

By taking inspiration from (1), a synthesis strategy is proposed for the case of planar arrays and ring shaped patterns which does not require the exploitation of global optimization procedures. In particular, the approach is able to determine a priori (that is, without solving the overall design problem) whether the given power pattern design constraints can be fulfllled or not, and, in the adflrmative case, to determine the needed excitation coe-cients in a fast deterministic manner. Although the approach does not apply to generic planar arrays and generic constraints, it applies to a large number of problems of actual interest, and outperforms some recently published synthesis procedures. Moreover, it may serve both as a reference solution for more general synthesis procedures, and as an elementary brick for more cumbersome synthesis problems.

Mask-constrained power synthesis of maximally sparse linear arrays through a compressive-sensing-driven strategy

We propose a new deterministic approach to the synthesis of linear arrays having the least possible number of elements while radiating shaped beams lying in completely arbitrary power masks. The approach takes joint advantage from compressive sensing (CS), from the multiplicity of power patterns lying in a given mask, and from the multiplicity of field solutions corresponding to each of these power patterns. Care is taken in order to exploit the available degrees of freedom in an effective fashion, and in optimizing parameters that affect the CS performance. An extensive numerical comparison against state-of-the-art procedures proves the effectiveness of the approach.

Optimizing Power Transmission in Given Target Areas in the Presence of Protection Requirements

We present a new approach to the synthesis of fields able to maximize the power radiated in an arbitrary portion of the visible space in the presence of protection requirements and constraints on the beam efficiency. As a by-product, beam efficiency can also be optimized if desired. The devised procedure works whether the target area has a linear, square, or circular footprint. The synthesis is stated in terms of a convex programming problem, with the related advantages in terms of both convergence speed and solutions optimality. The given theory is supported by numerical results including comparisons to state-of-the-art approaches.

Improving performances of Compressive Sensing in the synthesis of maximally-sparse arrays

Synthesizing antenna arrays with a minimum number of elements is a problem of high importance in different applications. A relevant contribution in solving such a problem is currently given by a number of synthesis techniques based on the Compressive Sensing (CS). For this reason, we present herein an innovative approach wherein fast pre-processing and post-processing techniques are proposed in order to further improve performance of CS in the design of linear arrays with shaped patterns. Numerical examples in support of the proposed processing procedure are also provided.

Optimization of the Array Element Layout for a Rotating Imaging Interferometer

In this paper, after a brief review on the working principles of synthetic aperture radiometers exploiting interferometry and mechanical rotation of the antenna, analytical expressions are provided which allow to easily compute the receiving performance of the interferometer starting from given locations of its sensors. Then, an innovative and general approach is developed and discussed for the optimal synthesis of the locations of the array sensors in order to fulfill requirements of crucial interest. Moreover, an innovative approach is also developed for the synthesis of the optimal weighting of the different collected signals. Finally, the performances of the developed synthesis approaches are discussed with reference to the GEO Atmospheric Sounder (GAS) array instrument.

Phase Retrieval by Constrained Power Inflation and Signum Flipping

In this paper we consider the problem of retrieving a signal from the modulus of its Fourier transform (or other suitable transformations) and some additional information, which is also known as ‘Phase Retrieval’ problem. The problem arises in many areas of applied Sciences such as optics, electron microscopy, antennas, and crystallography. In particular, we introduce a new approach, based on power inflation and tunneling, allowing an increased robustness with respect to the possible occurrence of false solutions. Preliminary results are presented for the simple yet relevant case of one-dimensional arrays and noisy data.

SATELLITE MULTIBEAM COVERAGE OF EARTH: INNOVATIVE SOLUTIONS AND OPTIMAL SYNTHESIS OF APERTURE FIELDS

The problem of the synthesis of optimal continuous aperture sources to optimally realize the satellite multibeam coverage of Earth is stated and solved. The design approach relies on a far-field representation which exploits at best the degrees of freedom arising from the geometrical structure of the well-known four-colors coverage map. The overall synthesis is stated as a Convex Programming problem wherein the fast achievement of the (unique) globally optimal solution is guaranteed. The introduced tools allow stating the ultimate theoretical radiation performances achievable by any circular-aperture antenna of fixed size and, at the same time, can be exploited as a reference in the synthesis of isophoric direct-radiating arrays. Numerical examples concerning a mission scenario recently proposed by the European Space Agency are provided.

Phase retrieval as a power inflation problem

This paper deals with a novel approach to determine the far field of a discrete source starting from the knowledge of far-field intensity data sets only. In particular, by taking advantage from a body of knowledge from antenna synthesis, as well as from the exploitation of suitable norms, we are able to formulate the problem as the superposition of (many) convex problems. Such a circumstance allows (at least in principle) to avoid false solutions.

Modeling and processing L-band ground based radar data for landslides early warning

L-band radars have been proposed as possible way for monitoring landslides. In this paper, we examine and solve the principal difficulties arising in modeling and processing radar data, evidencing differences with more usual SAR imaging. Numerical examples in support of the proposed processing procedure are finally provided.