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Synthesis of monopulse sub-arrayed linear and planar array antennas with optimized sidelobes
No full textIn this paper, three approaches for the synthesis of the optimal compromise between sum and difference patterns for sub-arrayed linear and planar arrays are presented. The synthesis problem is formulated as the definition of the sub-array configuration and the corresponding sub-array weights to minimize the maximum level of the sidelobes of the compromise difference pattern. In the first approach, the definition of the unknowns is carried out simultaneously according to a global optimization schema. Differently, the other two approaches are based on a hybrid optimization procedures, exploiting the convexity of the problem with respect to the sub-array weights. In the numerical validation, representative results are shown to assess the effectiveness of the proposed approaches. Comparisons with previously published results are reported and discussed, as well. “(c) The Electromagnetics Academy. The final version of this article is available at the url of the journal PIER (Progress In Electromagnetics Research) http://www.jpier.org/PIER/pier.php?paper=09092510
Synthesis of time-modulated planar arrays with controlled harmonic radiations
No full textThis paper presents a technique for the control of the sideband radiations in time-modulated planar arrays. The proposed method is aimed at generating a desired pattern at the carrier frequency as well as reducing the power losses and the interferences related to the harmonic radiations. By acting on both the durations and the commutation instants of the time pulses controlling the element switches, the method based on a Particle Swarm Optimizer is applied. Representative results are reported and discussed to show the effectiveness of the proposed approach
On the Exploitation of Analytic Sequences for Array Interleaving
No full textThis paper presents a methodology based on Almost Difference Sets (ADSs) for the design of shared aperture arrays with well behaved sidelobes. Thanks to the autocorrelation properties of ADSs, such a technique allows the design of fully interleaved arrays with predictable performances. Analytical and numerical results are provided in order to point out the computational efficiency and the effectiveness of the approach th in the linear and in the planar case
Innovative Approaches for Optimized Performance in Time-Modulated Linear Arrays
No full textIn time�]modulated arrays, time is exploited as an additional degree of freedom for the array synthesis in order to better control the radiated beam. More specifically, by properly turning on and off the array elements according to suitable time sequences, the synthesis of patterns with low side lobe levels (SLLs) [1�]2] is obtained and the opportunity of optimizing the array performances in time�]varying wireless scenarios enabled. Unfortunately, time�]modulated arrays generate undesired harmonics, the so�]called sideband radiations (SR), which represent a non�]negligible loss of radiated power [3]. In order to overcome such a drawback and to improve the performances of the array, evolutionary optimization approaches have been recently and successfully applied. In [4] and [5], a Differential Evolution (DE) algorithm has been used to optimize the static�]mode coefficients as well as the durations of the time pulses leading to a significant reduction of the sideband level (SBL). In [6], the minimization of the SLL at the carrier frequency and of the SBL in uniformly excited time�]modulated arrays has been performed by means of a Simulated Annealing (SA) technique. In such a framework, a Genetic Algorithm (GA) based strategy has been considered in [7] to optimize the time sequences where the modulation period was subdivided in shorter time steps. This paper presents an innovative approach based on a Particle Swarm Optimizer (PSO) aimed at further enhancing the performances of time�]modulated linear arrays in terms of SBL reduction. From the mathematical formulation of the problem at hand, it follows that two parameters controls the synthesis process: the switch�]on intervals (i.e., the durations of the rectangular time pulses of the time modulating sequence) and the switch�]on instants (the times when the excitation coefficients switch on). More in detail, since the principal pattern at the carrier frequency is a function of the switch�]on intervals, whereas the SBL depends by both the parameters, the target of the synthesis procedure is the optimization of the switch�]on instants to reduce the SBL for a given principal pattern (i.e., fixed switch�]on intervals). In the following, the problem is briefly formulated and some selected results are reported to assess the effectiveness of the proposed approach
An Integration Between SVM Classifiers and Multi-Resolution Techniques for Early Breast Cancer Detection
No full textBecause of the high contrast between the dielectric properties of normal and malignant breast tissues at microwave frequencies, microwave imaging techniques seem to be very attractive diagnosis methods for cancer detection [1][2]. In such a framework, inverse scattering methods are very promising tools, but their practical application is strongly limited by the need of 3D reconstructions, high spatial resolutions, and fast processing. Recently, to reduce the high computational costs and to fit the real‐time requirements, inversion methods based on learning by example techniques have been proposed [3]. LBE approaches based on support vector machines (SVMs) [3] and neural networks (NNs) [4] have been satisfactorily applied in various and complex electromagnetic problems. When dealing with breast cancer detection, the inversion process is recast as a classification or regression problem where the unknowns are retrieved from the data (i.e., the electric field samples collected in an external observation domain) by approximating the unknown relation data‐unknowns through an off‐line data fitting procedure (training phase). Once the training procedure (performed once and off‐line) is completed, the characteristics of the malignant breast tissue are real‐time estimated in the testing phase. In such a work, the detection problem is addressed by integrating a SVM‐based classifier with an iterative multi‐zooming procedure. More in detail, a succession of approximations of a probability map of the presence of pathology is determined. At each step, the spatial resolution of the risk‐map is improved in a limited set of regions of interest (ROIs) defined at the previous zooming step and characterized by a greater value of the occurrence probability of a malignant tissue. The multi‐step procedure is stopped when a stationary condition on the probability and on the number of ROIs is reached. The achievable trade‐off between computational complexity and spatial resolution is preliminary assessed by discussing a selected set of numerical simulations concerned with both noiseless as well as corrupted data
Optimization of Difference Pattern Features in Sub-Arrayed Monopulse Antennas Through and Excitations Matching Procedure
No full textRadar tracking operations are aimed at determining the flight path of a target. They are usually carried out by means of a “monopulse radar tracker” able to recover the position of the target by the reflected echo of a previously transmitted pulse [1]. Towards this purposes the antenna of the tracker system is required to generate two difference beams on the same aperture: a “sum” beam and a “difference” one
Three Dimensional Electromagnetic Sub-Surface Sensing by Means of a Multi-Step SVM-Based Classification Technique
No full textIn this paper, the classification approach is extended from 2D to the three‐dimensional(3D) case carefully addressing the increased complexity issue by means of an effective multi‐step strategy. As a matter of fact, by iteratively processing the training dataset (without requiring an extra amount of measurements), the proposed method is aimed at improving the spatial resolution of the original classification technique [6] even though dealing with a more complex problem. The effectiveness of the proposed approach has been preliminary assessed through a set of numerical experiments also in correspondence with blurred data and some representative results are shown in the following. This is the author's version of the final version available at IEEE
Reconstruction of Dielectric Objects from Amplitude - Only Data – Advantages and Open Problems of a Two-Step Multi-Resolution Strategy
No full textIn the following contribution an innovative strategy for the inversion of amplitude�]only data in microwave imaging applications is presented. The method consists of two steps. At the first step the source is synthesized in order to compute the incident field in the investigation domain. In the second step the profile of the object is reconstructed thanks to the iterative multi�]scaling approach combined to the Particle Swarm Optimiser, an innovative and effective evolutionary minimization technique. The effectiveness of the algorithm is preliminary assessed through the inversion of experimental data concerning an inhomogeneous dielectric scatterer
Analysis of the Potentialities and Limitations of the Integration Between the IMSA and the Level Set Method for Inverse Scattering
No full textIn the framework of the inverse scattering methodologies, this paper is aimed at preliminarily assessing the integration between the Iterative Multi-Scaling Approach and the Level-Set-based method. In order to enhance the potentialities of the Level-Set-based minimization, a multi-resolution procedure is employed for allowing a finer discretization only in those regions of interest where the scatterers are located thus reducing the whole computational burden with respect to a singe-resolution approach. In order to demonstrate the effectiveness of the IMSA Level Set technique, a set of representative numerical results are presented and discussed. This is the author's version of the final version available at IEEE
Smart Antennas Control in Complex Scenarios Through a Memory Enhanced PSO-Based Optimization Approach
No full textIn the framework of control methods for adaptive phased-arrays, this paper describes an innovative technique based on a memory enhanced optimization for dealing with complex scenarios and system models. Compared to other existing approaches working with far-field interferences, such a method focus on realistic situations where jamming sources are located both in the near-field or in the far-field of the antenna. Moreover, the effects of the mutual coupling are taken into account. A set of selected numerical results are presented in order to confirm the effectiveness of the proposed technique