Planar Thinned Arrays Research Articles

A Hybrid Taguchi Binary Particle Swarm Optimization for Antenna Designs

A hybrid Taguchi binary particle swarm optimization (HTBPSO) is proposed in this letter for electromagnetic optimization problems. The proposed algorithm combines the better properties of Taguchi method for updating the optimum positions of particles and improving the local search ability. To avoid premature convergence during the solution process, catfish effect operation is performed to alter the last 10% worse particle positions. Three examples, including the designs of linear and planar thinned arrays and planar triband monopole, are presented to demonstrate the efficiency of HTBPSO. As expected, experimental results show that HTBPSO achieves not only better solutions but also a faster convergence speed compared with the other two algorithms

An Improved Multi-Objective Genetic Algorithm for Large Planar Array Thinning

In this paper, a novel hybrid multi-objective optimization algorithm based on the nondominated sorting genetic algorithm II for large array thinning is presented. The iterative fast Fourier transform (IFFT) technique with a judge factor is introduced into the optimizer to accelerate the convergence. The global characteristics of a genetic algorithm show its optimization capability in the early phase of the optimization process and the powerful local search ability of IFFT works in the late phase. Thus, this proposed algorithm can not only effectively avoid being trapped into the local optimum but also possess a fast convergence for large array thinning. Several representative examples of large planar thinned arrays validate the good performance of the proposed algorithm.

Modified Compact Genetic Algorithm for Thinned Array Synthesis

In this letter, a new optimization algorithm, the Modified compact Genetic Algorithm (M-cGA) is introduced and applied to the synthesis of thinned arrays. The M-cGA has been derived from the compact Genetic Algorithm (cGA), properly modified and improved by implementing more than one probability vector (PV) and adding suitable learning scheme between these PVs. The so-obtained algorithm has been applied to the optimized synthesis of different-size linear and planar thinned arrays: In all the considered cases, it outperforms not only the cGA, but also the other optimization schemes previously applied to this kind of problem, both in terms of goodness of the solution (minimization of the peak sidelobe level) and of computational cost.

Erratum to “Orthogonal Genetic Algorithm for Planar Thinned Array Designs”

Li Zhang, Yong-Chang Jiao, Bo Chen, and Hong Li National Key Laboratory of Antennas and Microwave Technology, Xidian University, Xi’an, Shaanxi 710071, China Correspondence should be addressed to Li Zhang; lizhang@mail.xidian.edu.cn Received 21 May 2013; Accepted 27 June 2013 Copyright © 2013 Li Zhang et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Planar Thinned Arrays: Optimization and Subarray Based Adaptive Processing

A new approach is presented for the optimized design of a planar thinned array; the proposed strategy works with single antenna elements or with small sets of different subarray types, properly located on a planar surface. The optimization approach is based on the maximization of an objective function accounting for side lobe level and considering a fixed number of active elements/subarrays. The proposed technique is suitable for different shapes of the desired output array, allowing the achievement of the desired directivity properties on the corresponding antenna pattern. The use of subarrays with a limited number of different shapes is relevant for industrial production, which would benefit from reduced design and manufacturing costs. The resulting modularity allows scalable antenna designs for different applications. Moreover, subarrays can be arranged in a set of subapertures, each connected to an independent receiving channel. Therefore, adaptive processing techniques could be applied to cope with and mitigate clutter echoes and external electromagnetic interferences. The performance of adaptive techniques with subapertures taken from the optimized thinned array is evaluated against assigned clutter and jamming scenarios and compared to the performance achievable considering a subarray based filled array with the same number of active elements.

SYNTHESIS OF LARGE PLANAR THINNED ARRAYS USING IWO-IFT ALGORITHM

The iterative Fourier technique (IFT) is a high e-ciency method that was proposed in recent past for the synthesis of large planar thinned arrays with isotropic radiating elements. However, the selection mechanism of IFT cannot always include the most useful elements in the \turned ON families, which make the method trap in some local minima. Therefore, in this paper, inspired by invasive weed optimization (IWO) algorithm, a developed version of the iterative Fourier technique (IFT), IWO-IFT, is proposed for thinning large planar arrays. In this new method, the initial weeds are produced by IFT, and are further perturbed by IWO through repeatedly reproduction, dispersion, and exclusion over search space to flnd better weeds. Numerical results for synthesizing difierent circular thinned arrays demonstrated the superiority of IWO-IFT over the IFT method.

Orthogonal Genetic Algorithm for Planar Thinned Array Designs

An orthogonal genetic algorithm (OGA) is applied to optimize the planar thinned array with a minimum peak sidelobe level. The method is a genetic algorithm based on orthogonal design. A crossover operator formed by the orthogonal array and the factor analysis is employed to enhance the genetic algorithm for optimization. In order to evaluate the performance of the OGA, 20×10-element planar thinned arrays have been designed to minimize peak sidelobe level. The optimization results by the OGA are better than the previously published results.

Design of planar thinned arrays using a Boolean differential evolution algorithm

As a very powerful optimisation approach, differential evolution algorithm for continuous optimisation problems has been applied to electromagnetic (EM) design problems. However, the optimisation of a thinned array can be formulated as a discrete-variable optimisation problem with solutions encoded as binary strings. Here, a Boolean differential evolution (BDE) algorithm for 0–1 integer programming problems is proposed to design planar thinned arrays with minimum sidelobe levels. The BDE algorithm with only one control parameter is easily implemented. Meanwhile, a fast Fourier transform is employed to speed up the calculation of the pattern. Numerical experiments show that the BDE algorithm is an effective technique.