Antenna Array Synthesis Research Articles

Efficient synthesis of 4D antenna arrays using a bitwise evolutionary genetic algorithm

In this paper, a bitwise evolutionary genetic algorithm GA is proposed to synthesize the power patterns of 4D antenna arrays efficiently. Within the binary optimized time sequences of 4D antenna arrays, the genes of 1 and 0 represent switch-on and switch-off period of antennas, respectively. Gene retention probability, which relates to the fitness values of each individual in the whole group, is proposed to evaluate how good each gene is. With the proposed gene retention probability, the crossover operator in traditional GA is replaced with a new method to generate the next generation. The proposed algorithm is applied to the synthesis of 4D antenna arrays with binary optimized time sequences, and the performance of the proposed algorithm is compared with that of traditional GA on the condition of the same parameter settings. The comparison results show that bitwise evolutionary GA improves the optimization efficiency significantly, which reduces the computation time as much as 85% on average of the traditional GA with the same goal. Copyright © 2014 John Wiley & Sons, Ltd.

향상된 적응형 유전 알고리즘을 이용한 컨포멀 배열 안테나의 빔 합성 연구

본 논문에서는 2차 함수 곡선의 회전체 곡면 위에 있는 배열 안테나의 빔 합성을 위한 Enhanced Adaptive Genetic Algorithm(EAGA)을 제안하였다. 제안된 알고리즘은 더 빠른 수렴 속도와 더 낮은 비용함수 값을 얻기 위해 Adaptive Genetic Algorithm(AGA)과 Invasive Weed Optimization(IWO)을 결합시켰다. 각 안테나 소자의 급전 크기와 위상의 최적화된 값은 EAGA를 통해 구하였으며, 이 결과를 통해 EAGA가 컨포멀 배열 안테나의 패턴 합성 알고리즘으로써 AGA보다 더 우수함을 보였다. This paper proposes an enhanced adaptive genetic algorithm(EAGA) dedicated to pattern synthesis of array antenna which conforms to a curved surface of rotation with quadratic function. EAGA combines adaptive genetic algorithm(AGA) with invasive weed optimization(IWO) for the faster convergence and the lower cost value of the cost function. The amplitude and phase of each excited weighting factor are optimized to meet the required goals using EAGA. The EAGA results indicate that the proposed algorithm is superior to AGA when applied to the problem of conformal array antenna pattern synthesis.

A quantized water cycle optimization algorithm for antenna array synthesis by using digital phase shifters

In this article, a quantized water cycle algorithm (QWCA) is used for the antenna array pattern synthesis with low side-lobe levels (SLLs) and nulls at desired directions by using four-bit digital phase shifters. In addition to the standard features as a metaheuristic algorithm, QWCA has an internal quantization mechanism and a precalculated array factor method. The latter provides an accelerated procedure to QWCA under favour of the digitized values that can be stored in a three-dimensional array. This acceleration is based on the reality that the accessing data in the memory need less time than the usage of the mathematical functions throughout the optimization process. The internal quantization mechanism of QWCA is utilized to achieve digital values matching to the discrete values of the phase shifter instead of the simple rounding up/down routines after optimization. The numerical results showed that QWCA can obtain very good SLLs and null depth levels (NDLs) on the synthesized pattern. Moreover, the results are achieved in remarkably short optimization times. SLL and NDL values obtained by QWCA are also compared with the available literature values. The comparisons reveal that QWCA is able to produce better results than the other compared alternatives. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:21–29, 2015.

Conformal antennas arrays radiation synthesis using immunity tactic

Purpose – The purpose of this paper is to introduce to scientific community a new optimization technique and its application to the radiation synthesis case. Design/methodology/approach – The immunity tactic is a new powerful optimization tool inspired by immune system. It was used with success to achieve the conformal antenna radiation synthesis in an acceptable processing time. Findings – Radiation synthesis of conformal antenna arrays based on immunity tactic generates very good results compared with other optimization methods. The comparison is very satisfactory as regards accuracy and processing time. Research limitations/implications – The improvement of convergence and accuracy will be done certainly by use of other variants of the technique or combination with others. Originality/value – The paper exposes with details a new optimization technique based on immune system and its behavior. The results, for the special case of conformal antenna arrays radiation synthesis, are very satisfactory and very encouraging. The impact of the new technique will be, without doubt, positive on optimization field.

Synthesis of a Near-Optimal High-Gain Antenna Array With Main Lobe Tilting and Null Filling Using Taguchi Initialized Invasive Weed Optimization

A near-optimal base-station antenna array synthesis suitable for broadcasting applications is presented. The array is required to provide a high-gain radiation pattern with a main lobe slightly tilted from the horizontal plane and null filling inside an angular sector under the main lobe. To satisfy the above requirements, a novel invasive weed optimization (IWO) variant called Taguchi initialized IWO (TI-IWO) is proposed in this paper. In TI-IWO, the Taguchi's optimization method is employed to initialize effectively the positions of the weeds used by the IWO method. In this way, the fitness function starts from lower values and, thus, the TI-IWO method finds better near-optimal solutions than the conventional IWO method. The proposed method has been applied to linear arrays. Due to its easy implementation in practice, a uniform-amplitude excitation distribution is considered to be applied on the array elements. Two cases of isotropic source arrays are studied under specific requirements for maximum possible gain, main lobe tilting, and null filling. Also, the TI-IWO method is applied to optimize realistic cases of collinear wire dipole arrays in front of a mast under the same requirements and an additional one concerning the impedance matching of all the dipoles.

Unified particle swarm optimization with random ternary variables and its application to antenna array synthesis

Antenna array synthesis sometimes involves both real and integer parameters as a mixed integer optimization problem. In this paper, a modified particle swam optimization (PSO) algorithm is proposed in order to deal with real and integer variables in a unified manner. Two major modifications are made compared to the classical PSO algorithm. First a unified vector having continuous values between 0 and 1 is defined, and at each iteration this vector (or part of it) is mapped to real variables and/or rounded to integer variables, which makes the updating process unified for any type of parameters. Second, random ternary variables are introduced to compensate quantization errors caused by the rounding-off operations, which could accelerate the speed of convergence and lead to improved topology exploration capability. In order to demonstrate the effectiveness of the proposed method, three previous examples about antenna array synthesis are revisited, and better results than those in the existing literatures are obtained in all these examples.

Certain investigations on the reduction of side lobe level of an uniform linear antenna array using biogeography based optimization technique with sinusoidal migration model and simplified-BBO

In this paper, we propose biogeography based optimization technique, with linear and sinusoidal migration models and simplified biogeography based optimization (S-BBO), for uniformly spaced linear antenna array synthesis to maximize the reduction of side lobe level (SLL). This paper explores biogeography theory. It generalizes two migration models in BBO namely, linear migration model and sinusoidal migration model. The performance of SLL reduction in ULA is investigated. Our performance study shows that among the two, sinusoidal migration model is a promising candidate for optimization. In our work, simplified – BBO algorithm is also deployed. This determines an optimum set value for amplitude excitations of antenna array elements that generate a radiation pattern with maximum side lobe level reduction. Our detailed investigation also shows that sinusoidal migration model of BBO performs better compared to the other evolutionary algorithms discussed in this paper.

Linear Antenna Array Synthesis Using Mean Variance Mapping Method

A mean variance mapping optimization algorithm for three types of antenna array synthesis examples is presented. Mean variance mapping optimization is based on the strategic transformation used for mutating the offspring built on mean variance of a certain dynamic population. The first set of examples is based on side-lobe suppression and null control by controlling element positions with mean variance mapping optimization under constraints to beam width. In the second group of examples, mean variance mapping optimization becomes an optimization tool to calculate the amplitude and phase values of antenna array elements to synthesize shaped beams. In the last set of examples, mean variance mapping optimization is used to mitigate the effect of failure elements on the pattern by recalculating the amplitude values of remaining elements. Additionally, a modification that provides a good balance between exploitation and exploration is applied to the mean variance mapping optimization algorithm to improve its stability and accuracy. The simulation results showed that the proposed mean variance mapping optimization is an effective and easy implementable technique for different antenna array synthesis problems.

Synthesis of a Linear Antenna Array for Maximum Side-lobe Level Reduction

are number of Techniques used to reduce Side Lobe Level (SLL) of antenna arrays to save power and improve Quality of Service (QoS) by ensuring maximum radiation in desired direction, several methods are available in literature. It is a well known fact that when an attempt is made to reduce the first sidelobe level of an antenna array, the beamwidth increases. However, in the present work, an array for a specified first side lobe level of -35dB was synthesized using Dolph Chebyshev method. A real-value Genetic Algorithm (RGA) was also used to optimize the current excitations. The weighting vectors are compared. Using these vectors, patterns are generated for arrays of different elements. The resultant patterns are compared and the result shows greater improvement in the SLL reduction from the RGA method without deteriorating the main beamwidth. Keywordslobe level, Quality of Service, beamwidth, Dolph Chebyshev, and Real-Value Genetic Algorithm 1. INTRODUCTION antenna array is a group of identical antenna elements

Linear antenna array synthesis using cat swarm optimization

Abstract Antenna arrays with high directivity and low side lobe levels need to be designed for increasing the efficiency of communication systems. A new evolutionary technique, cat swarm optimization (CSO), is proposed for the synthesis of linear antenna arrays. The CSO is a high performance computational method capable of solving linear and non-linear optimization problems. CSO is applied to optimize the antenna element positions for suppressing side lobe levels and for achieving nulls in desired directions. The steps involved in the problem formulation of the CSO are presented. Various design examples are considered and the obtained CSO based results are validated by comparing with the results obtained using particle swarm optimization (PSO) and ant colony optimization (ACO). The flexibility and ease of implementation of the CSO algorithm is evident from this analysis, showing the algorithm's usefulness in electromagnetic optimization problems.

Synthesis of Volumetric Ring Antenna Array for Terrestrial Coverage Pattern

This paper presents a synthesis of a volumetric ring antenna array for a terrestrial coverage pattern. This synthesis regards the spacing among the rings on the planes X-Y, the positions of the rings on the plane X-Z, and uniform and concentric excitations. The optimization is carried out by implementing the particle swarm optimization. The synthesis is compared with previous designs by resulting with proper performance of this geometry to provide an accurate coverage to be applied in satellite applications with a maximum reduction of the antenna hardware as well as the side lobe level reduction.

Antenna Array Synthesis and Failure Correction Using Differential Search Algorithm

Differential search (DS) optimization algorithm is proposed for the synthesis of three different types of linear antenna array design examples. The first group of examples is that DS algorithm is used to locate wide nulls on the linear antenna array patterns by controlling amplitude-only. In these examples, sidelobe levels disposed to rise are also suppressed by using DS algorithm in the same optimization process. In the second group of examples, individual nulls are placed with the help of DS algorithm by controlling the amplitude-only, phase-only, and position-only. The last example is a linear antenna array failure correction example. In order to tolerate the element failures, DS is employed to recalculate the amplitude values of the remaining intact elements of the antenna array. The results show that DS is very capable to solve the linear antenna array optimization problems which have different characteristics.

Comparative Studies on Generation of Stair Step Radiation Patterns

Antenna array synthesis is usually done by controlling amplitude and phase levels or element spacing functions of the array to get the desired characteristics of the radiation pattern. In this paper, design of equispaced linear array of dipoles is presented. A new amplitude distribution is proposed for generation of stair step patterns with zero phase. These patterns are produced from dipole elements using Fourier transform method. The goal of the work is to compensate mutual coupling effects of a linear dipole array. The computed patterns are compared with those of the isotropic elements for different number of elements. The deviation in the patterns of array of isotropic radiators and the array of practical element is found to be minimum. These patterns are used to identify multiple targets moving in different altitudes and different angular regions.

Backtracking Search Optimization Algorithm for Synthesis of Concentric Circular Antenna Arrays

A backtracking search optimization algorithm (BSA) is proposed for the synthesis of concentric circular antenna arrays (CCAAs) with the low sidelobe levels at a fixed beamwidth. Several numerical examples of CCAA patterns with the single, multiple, and broad nulls imposed at the directions of interference are also given to illustrate the performance and flexibility of the proposed algorithm. BSA is a relatively new population based evolutionary optimization algorithm. The numerical results show that the design of CCAA using BSA provides good sidelobe levels with a fixed beamwidth. The nulling patterns obtained by BSA are also very good. The quality of results obtained by the BSA is checked by comparing with that of several metaheuristic algorithms in the literature. BSA is also compared with differential search (DS) and bacterial foraging algorithms (BFA) in terms of iterative performances.

Pattern Synthesis of Planar Nonuniform Circular Antenna Arrays Using a Chaotic Adaptive Invasive Weed Optimization Algorithm

A novel invasive weed optimization (IWO) variant called chaotic adaptive invasive weed optimization (CAIWO) is proposed and applied for the optimization of nonuniform circular antenna arrays. A chaotic search method has been combined into the modified IWO with adaptive dispersion, where the seeds produced by a weed are dispersed in the search space with standard deviation specified by the fitness value of the weed. To evaluate the performance of CAIWO, several representative benchmark functions are minimized using various optimization algorithms. Numerical results demonstrate that the proposed approach improves the performance of the algorithm significantly, in terms of both the convergence speed and exploration ability. Moreover, the scheme of CAIWO is employed to find out an optimal set of weights and antenna element separation to obtain a radiation pattern with maximum side-lobe level (SLL) reduction with different numbers of antenna element under two cases with different purposes. The design results obtained by CAIWO have comfortably outperformed the published results obtained by other state-of-the-art metaheuristics in a statistically meaningful way.

Synthesis of Non-Uniform Amplitude equally Spaced Antenna Arrays Using PSO and DE Algorithms

In recent years Evolutionary computation has its growth to extent. Synthesis of non-uniform linear antenna arrays is one of the most important electromagnetic optimization problems of the current interest. In this paper, the design of non-uniform linear antenna arrays with optimum side lobe level reduction is investigated. Two global evolutionary optimization methods are Particle Swarm Optimization algorithm(PSO) and Differential Evolution algorithm(DE ) are used to determine an optimum set of weights and positions that provide a radiation pattern with optimum side lobe level having uniform progressive phase between the elements. Simulation results show considerable enhancements in array performances using the global optimizers. The paper finally illustrates a comparative evaluation of the two proposed algorithms regarding their applicability as numerical optimization techniques.

Application of Hybrid Optimization Algorithm in the Synthesis of Linear Antenna Array

The use of hybrid algorithms for solving real-world optimization problems has become popular since their solution quality can be made better than the algorithms that form them by combining their desirable features. The newly proposed hybrid method which is called Hybrid Differential, Particle, and Harmony (HDPH) algorithm is different from the other hybrid forms since it uses all features of merged algorithms in order to perform efficiently for a wide variety of problems. In the proposed algorithm the control parameters are randomized which makes its implementation easy and provides a fast response. This paper describes the application of HDPH algorithm to linear antenna array synthesis. The results obtained with the HDPH algorithm are compared with three merged optimization techniques that are used in HDPH. The comparison shows that the performance of the proposed algorithm is comparatively better in both solution quality and robustness. The proposed hybrid algorithm HDPH can be an efficient candidate for real-time optimization problems since it yields reliable performance at all times when it gets executed.

Comparative Analysis of Linear and Nonlinear Pattern Synthesis of Hemispherical Antenna Array Using Adaptive Evolutionary Techniques

Hemispherical antenna arrays are subjected to linear and nonlinear synthesis and are optimized using adaptive based differential evolution (ADE) and fire fly (AFA) algorithm. The hemispherical shaped array with isotropic elements is considered. Antenna element parameters that are used for synthesis are excitation amplitude and angular position. Linear synthesis is termed as the variation in the element excitation amplitude and nonlinear synthesis is process of variation in element angular position. Both ADE and AFA are a high-performance stochastic evolutionary algorithm used to solveN-dimensional problems. These methods are used to determine a set of parameters of antenna elements that provide the desired radiation pattern. The effectiveness of the algorithms for the design of conformal antenna array is shown by means of numerical results. Comparison with other methods is made whenever possible. The results reveal that nonlinear synthesis, aided by the discussed techniques, provides considerable enhancements compared to linear synthesis.

Two-Dimensional Time-Domain Antenna Arrays for Optimum Steerable Energy Pattern with Low Side Lobes

This document presents the synthesis of different two-dimensional time-domain antenna arrays for steerable energy patterns with side lobe levels. The research is focused on the uniform and nonuniform distributions of true-time exciting delays and positions of antenna elements. The uniform square array, random array, uniform concentric ring array, and rotated nonuniform concentric ring array geometries are particularly studied. These geometries are synthesized by using the well-known sequential quadratic programming. The synthesis regards the optimal true-time exciting delays and optimal positions of pulsed antenna elements. The results show the capabilities of the different antenna arrays to steer the beam in their energy pattern in time domain and how their performance is in frequency domain after the synthesis in time domain.

Synthesis of Cosecant and Square Patterns for EMC applications

Many researchers made an attempt on Beam shaping of antennas useful for different applications in surveillance and tracking radars. In the present work, synthesis of line source and linear antenna array with uniform current amplitudes and weight functions is discussed. An iterative sampling method approach is being considered for implementation. In an iterative method, original radiation pattern which is close to the desired radiation pattern is generated by a standard synthesis method and a series of correction patterns are applied to it by adding correction patterns until the convergence is achieved. The iterative method is implemented for both line source and linear array for generating cosecant and square radiation patterns and their results are compared. The patterns designed are found to exhibit minimum suitable levels and they are useful to instigate the problems of EMC.