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Summary: This study presents a novel method for reducing return loss and achieving lower side lobe levels in small planar antenna arrays (PAAs). Quantum particle swarm optimisation (QPSO) findings are utilised for antenna design modelling and performance assessment utilising the MATLAB‐based moment's code approach and MATLAB‐HFSS interface. The mutual coupling between antenna components is considered and computed using the method of moments (MoM). Changing the array elements' length and spacing will accomplish the abovementioned objectives. The Matlab‐based moments code calculates the antenna components' length and spacing, and the antennas' length and spacing are used to produce the radiation pattern via the Matlab‐HFSS interface. Four examples of small PAA designs are given to illustrate how well the applied methodology works. The method discussed in this paper is generic and can be employed in the future for different sizes of the array elements and the different antenna array structure designs. [ABSTRACT FROM AUTHOR]

A high gain antenna array with reduced side lobe level (SLL) needs to be optimized and designed to meet the requirement of modern wireless communication systems. To achieve this goal, a newly developed natural heuristic algorithm namely sparrow search algorithm (SSA) and its modification are introduced and utilized to the field of electromagnetic optimization for the first time in this paper. Simulation results over several different examples of the linear antenna array (LAA) and circular antenna array (CAA) design problem have been presented to demonstrate the effectiveness and superiority of the modified SSA. The design results obtained by modified SSA showed greater advantages than those certain classical and well-known algorithms like particle swarm optimization (PSO), whale optimization algorithm (WOA) and grasshopper optimization algorithm (GOA), in a statistically meaningful way. [ABSTRACT FROM AUTHOR]

Summary: A novel synthesis method to reduce the maximum side lobe in the entire azimuth plane and for achieving a desired value of directivity of a concentric elliptical array antenna is addressed in this paper. Three well‐performing meta‐heuristic optimization algorithms, teaching learning‐based optimization (TLBO), symbiotic organism search (SOS), and quantum particle swarm optimization (QPSO), are employed to optimize the cost function and to obtain the desired radiation pattern. Different simulation‐based experiments are performed to obtain the best possible set of angular positions and the distribution of isotropic antennas across the ellipses by rigorously maintaining non‐overlapping constraints. The major benefit of the proposed design is the deprecation of interference in all phi planes. The statistical analysis of the simulation results demonstrate perceptible improvement compared with that of a uniformly spaced concentric elliptical array and hence show the efficiency of the proposed algorithms. In both simulation studies, the results obtained using TLBO, SOS, and QPSO are compared. Analysis of the results exhibits that for the stated objective, the TLBO‐ and SOS‐based side lobe reduction approach performs superior to QPSO method. Proposed multi‐objective research work could lead to reduce payload and can simultaneously achieve isoflux coverage in entire azimuth plane on the earth surface which can essentially be utilized in (Low Earth Orbit) LEO and (Geostationary Earth Orbit) GEO satellites applications. [ABSTRACT FROM AUTHOR]

A novel method of designing unequally spaced time-modulated arrays (UESTMAs) by handling fewer optimization parameters with reduced problem dimension is presented in this paper. For synthesizing UESTMA, two design parameters, specifically, the non-linear parameter - element position, and the linear parameter - on-time durations are optimized in two steps. Different possible cases of linear and non-linear synthesis methods such as, positiononly (PO), on-time only (OTO), position then on-time (PTOT), on-time then position (OTTP), and simultaneous position on-time (SPOT) are considered. To examine the performance of the synthesis methods, three global search stochastic algorithms based on differential evolution (DE), teaching-learning-based optimization (TLBO) and quantum particle swarm optimization (QPSO) have been employed to achieve the array pattern with significantly suppressed side lobe levels and sideband levels. Through comparative study, it is observed that the two step nonliner to linear synthesis method by fewer optimization parameters is efficient to provide better pattern with less computation time. [ABSTRACT FROM AUTHOR]

Today, the design of antenna arrays is very important in providing effective and efficient wireless communication. The purpose of antenna array synthesis is to obtain a radiation pattern with a low side lobe level (SLL) at a desired half power beam width in far-field. The amplitude and position values of the array elements can be optimized to obtain a radiation pattern with suppressed SLLs. In this paper, swarm-based metaheuristic algorithms including particle swarm optimization (PSO), artificial bee colony (ABC), mayfly algorithm (MA) and jellyfish search (JS) are compared to determine the optimal design of linear antenna arrays. Extensive experiments are conducted on designing 10-, 16-, 24- and 32-element linear arrays by determining the amplitude and positions. Experiments are repeated 30 times due to the random nature of swarm-based optimizers, and statistical results show that the performance of the novel algorithms, MA and JS, is better than that of the well-known PSO and ABC methods. [ABSTRACT FROM AUTHOR]

This article shows the design of a non‐uniformly excited single ring circular antenna array (CAA) for the synthesis of optimal far‐field radiation characteristics. A recently proposed meta‐heuristic based optimization algorithm called gray wolf optimization (GWO) and state‐of‐the‐art swarm intelligence based evolutionary optimization technique known as particle swarm optimization with a distribution based update mechanism (PSOd) are individually applied to determine the optimum set of current excitation amplitude weights and the inter‐element spacing among the array elements to reduce the side lobe level and 3‐dB beamwidth considering the mutual coupling. The results obtained by employing PSOd and GWO are compared to those of the uniform radiation pattern and the recently published results of state‐of‐the‐art literature having equal sets of elements to show the superiority of employed approaches. Three different design examples of 8, 10, and 12 elements CAA are reported in this article to study the performances of PSOd and GWO algorithm‐based results over the results of other recently reported literature. [ABSTRACT FROM AUTHOR]

Nature inspired algorithms are finding extensive applications in real-world applications. Firefly algorithm (FA) is one such swarm intelligent algorithm introduced in the recent past. This algorithm has proved its competitiveness over standard benchmark and real-world applications, but suffers from the problem of slow convergence speed. So, in order to overcome this problem, a modified FA approach called enhanced firefly algorithm (EFA) is proposed. The performance of the proposed EFA with respect to FA and other algorithms has been evaluated for eleven benchmark functions. The numerical results show that the novel method consistently provides better solution at a faster rate. Moreover, as a real-world application, EFA has been used for synthesis of linear antenna array for both equally and unequally spaced arrays. The results demonstrate that EFA provides reduced sidelobe level and faster convergence in comparison with algorithms like FA, biogeography-based optimization, cuckoo search, differential evolution, genetic algorithm, particle swarm optimization, tabu search and Taguchi method. [ABSTRACT FROM AUTHOR]

In this paper, a novel algorithm, namely bat flower pollination (BFP) is proposed for synthesis of unequally spaced linear antenna array (LAA). The new method is a combination of bat algorithm (BA) and flower pollination algorithm (FPA). In BFP, both BA and FPA interact with each other to escape from local minima. The results of BFP for solving a set of 13 benchmark functions demonstrate its superior performance as compared to variety of well-known algorithms available in the literature. The novel proposed method is also used for the synthesis of unequally spaced LAA for single and multi-objective design. Simulation results show that BFP is able to provide better synthesis results than wide range of popular techniques like genetic algorithm, differential evolution, cuckoo search, particle swarm optimization, back scattering algorithm and others. [ABSTRACT FROM AUTHOR]

In an antenna array due to large number of elements, there is always a possibility of failure of one or more elements in the array system, which results in increased SLL with distorted radiation pattern. Recovering the optimal beam pattern can be done by recalculating the amplitude distributions for array elements leaving the failed elements. Here, we have corrected the radiation pattern for concentric circular antenna array (CCAA) with central element, as CCAA with central element is widely implemented in smart antennas and mobile communication. A central element has been added to array to increase the steering capability of proposed array. It has been noticed that after failure of three or more number of elements with central element, there is a significant increase in side lobe level (SLL) which degrades the performance of the system. This distortion is corrected using bacterial foraging optimization, standard particle swarm optimization (PSO), and crazinessbased particle swarm optimization (CRPSO) technique. The results of standard PSO and CRPSO are compared for a three ring CCAA with central element and it has been concluded that CRPSO gives the optimum result. [ABSTRACT FROM AUTHOR]

In this paper the steerable isotropic circular array antenna is designed for reducing the side lobe level (SLL) using evolutionary optimization technique. The optimization techniques particle swarm optimization and cat swarm optimization algorithm are used to reduce the SLL as well as to steer the main beam in specific direction. In this design of steerable circular arrays the amplitude excitations are optimized. Obtained results show that the maximum peak of SLL of the resultant patterns are as per requirement. This paper present a good performance in the array factor response and suppressed SLL for different number of array elements with different steering angle of the main beam using evolutionary optimization technique. [ABSTRACT FROM AUTHOR]

In this paper, optimal design of single-ring and multi-ring circular array, hexagonal array, and elliptical array of isotropic antenna has been carried out using Simplex Particle Swarm Optimization (Simplex-PSO). The synthesis of the array geometry is first formulated as an optimization problem with the goal of side lobe level reduction and is then solved using Simplex-PSO algorithm for optimum current excitations. To overcome the premature convergence characteristic of PSO, Simplex-PSO is considered while preserving the fast converging property of PSO. Two design examples are presented which illustrate the effectiveness of Simplex-PSO algorithm, and the optimization goal for each example is easily achieved. The design results obtained using Simplex-PSO are superior to those obtained using popular algorithms like PSO and its variant craziness-based PSO (CRPSO) and PSO with aging leader and challengers (ALC-PSO) in a statistically significant way. [ABSTRACT FROM AUTHOR]

This paper presents a design of fractal antenna arrays based on circular arrays of circular subarrays for scannable pattern using rotational symmetry properties of the complex feeding excitations for a maximum performance in terms of side lobe level (SLL) and directivity (DIR). This fractal array design considers the optimization of the amplitude and phase excitations exploiting the fractal characteristics of the geometry (rotational symmetry) in order to generate a scannable pattern. The synthesis process is carried out by the method of Differential Evolution (DE). The main advantages of using rotational symmetry are that the optimal excitations for a particular beam steering angle could be applied to other beam steering angles remaining in the same array factor characteristics (SLLand directivity) for every beam steering angle. This design of fractal antenna arrays provides a complete scanning of the azimuth plane with optimal characteristics of the radiation pattern using just one optimal design vector of amplitude and phase excitations. Furthermore, the performance of the fractal antenna array optimized with DE is compared with respect to the cases of Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and the conventional progressive phase for the same array geometry. [ABSTRACT FROM PUBLISHER]

This paper describes a method using Quantum Particle Swarm Optimization to obtain a broadband frequency invariant pattern for synthesis of nonuniformly spaced linear array of isotropic antennas. Two cases related to this work using QPSO have been studied, namely, in the first case, the generated frequency invariant far-field pattern is broadside in the vertical plane and in the second case, the far-field frequency invariant pattern is scanned in a particular direction. An effort is made such that the side lobe level and first null beam widths of the patterns are made similar to their related desired values. The two cases are presented in this paper to show the effectiveness of the proposed method in achieving the desired specifications. Even though, the developed method is utilized here for a linear array of isotropic antennas; it can be extended to other type of arrays. The performance of this algorithm is validated by duly comparing it with firefly algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a steerable isotropic circular array antenna is designed to reduce the side lobe level (SLL), using an evolutionary optimization technique. Particle swarm optimization and the firefly algorithm are used to reduce the SLL, as well as to steer the main beam in a specific direction. In this steerable circular array design, the amplitude excitations are optimized. The results show that the maximum SLL peak of the resultant patterns is as per requirements. Good performance is achieved in the array factor response and suppression of SLL for different numbers of array elements with different main beam steering angles. [ABSTRACT FROM AUTHOR]

This work presents a method based on quantum particle swarm optimization (QPSO) for the synthesis of a linear array of non-uniformly spaced parallel unequal length very thin dipole antennas for impedance matching of all the antenna elements in the array. This technique is used along with the generation of the radiation pattern with low side lobe level and main lobe tilting including uniform null filling (NF) which is generally useful for broadcasting applications. Mutual coupling effect exists between the parallel dipole antennas and it is analyzed using induced electro-motive force (EMF) method, assuming the distribution of the current on each and every dipole to be sinusoidal. To obtain the desired results, current excitation, length of the antenna and spacing between the antennas are taken as the optimizing parameters and QPSO as the optimizing algorithm. Two examples are presented to show the effectiveness of the proposed method. The performance of this algorithm for impedance matching is validated by duly comparing it with a standard benchmark algorithm. [ABSTRACT FROM AUTHOR]

A method based on quantum particle swarm optimization is proposed for correcting radiation pattern of a uniformly spaced linear array of parallel half-wavelength vertical very thin dipole antennas when more than one element of the array is completely defective. The generated pattern is broadside in the horizontal plane. Mutual coupling between the half-wavelength parallel dipole antennas has been taken care of by induced EMF method considering the current distribution on each dipole to be sinusoidal. Side lobe level and minimum return loss of the corrected pattern with defective elements are also calculated and an attempt is made that these parameters be equal to their respective specified values. This is usually done by changing excitation current amplitude of the non-defective elements without replacing the faulty elements. The element pattern of half-wavelength dipole antenna has been assumed omni-directional in the horizontal plane. Two examples are presented to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the beam steerable isotropic Linear Antenna Array is designed for reducing the side lobe level using evolutionary optimization technique. The optimization techniques particle swarm optimization (PSO) and Novel PSO are used to reduce the side lobe level (SLL) as well as to steer the main beam in specific direction. In this design of steerable Linear arrays, the amplitude excitations are optimized. Obtained results show that the maximum peak of SLL of the resultant patterns is as per requirement. This paper presents a good performance in the array factor response and suppressed SLL for different numbers of elements and different values of the steering angle of direction of the main beam with evolutionary optimization. [ABSTRACT FROM AUTHOR]

Two methods of side lobe reduction for linear phased array antenna are described in this paper. In the first case, side lobe of linear phased array is reduced by optimization using real coded genetic algorithm (RGA) and particle swarm optimization (PSO) with non-linear amplitude weight. In the second case, side lobe is reduced by array thinning technique using binary genetic algorithm (BGA) and binary particle swarm optimization (BPSO). Using RGA, maximum side lobe reduction of about 6dB and using PSO, maximum side lobe reduction of 7dB is achieved compared to uniform linear array (ULA). In array thinning, maximum side lobe reduction of about 4dB is obtained for BGA and BPSO compared to uniform linear array (ULA). [ABSTRACT FROM AUTHOR]

In this article, non-uniformly excited linear arrays are optimised using Taylor distribution and classical particle swarm optimisation (CPSO) algorithm for obtaining desired equal side lobe level (SLL). Elements of the array are considered to be isotropic in nature with uniform interelement spacing. Excitation amplitudes of each element are taken as optimisation parameters. Taylor distribution defines the range of excitation amplitude in which CPSO algorithm searches for the optimum value of excitation amplitude, with the objective of obtaining desired equal SLL. The proposed method eliminates the initial randomness of defining search space for CPSO algorithm. Comparison with other methods has been made whenever possible. The results reveal that the proposed method can be used to obtain the desired SLL. [ABSTRACT FROM AUTHOR]

In this article, a new method of pattern synthesis of centre fed, equal distance linear array having single and multiple synthesis objectives has been proposed and statistically investigated. Single objective of reduced side lobe level (SLL) and first null beamwidth (FNBW) has been considered separately. Consequently, multiple objectives of beamwidth and side lobe level have been investigated. Synthesis of linear array for suitable objectives has been investigated on Taylor one parameter distribution with equal progressive phase. Excitation amplitude of each array element is taken as optimization parameter where distribution has been optimized using Particle Swarm Optimization (PSO) for achieving low SLL. Later the same has been incorporated for obtaining suitable FNBW. In our optimization algorithm conventional PSO has been modified with a restricted search PSO (RSPSO) where search space has been predefined within excitation amplitude range. PSO within the defined range searches for optimum excitation amplitude to achieve the desired objectives. In order to illustrate the effectiveness of the proposed RSPSO, simulation results of three significant instances of linear array have been presented for both even and odd number of element. The design results obtained using RSPSO have improved result than those obtained using other state of the art evolutionary algorithms like differential evolution (DE), invasive weeds optimization (IWO) and Conventional particle Swarm optimization (CPSO) in a statistically significant way. [ABSTRACT FROM AUTHOR]

In this paper, the authors have proposed a method based on Quantum Particle Swarm Optimization (QPSO) algorithm in the context of radiation pattern correction of a linear array of isotropic antennas corrupted with one or more faulty antenna elements. Care is taken to maintain the values of side lobe level and maximum Wide Null Placement of the corrected pattern to be identical to the values of nondefective radiation pattern. This correction is made possible by altering the beam weights of the remaining elements in the array. The advantage of this method is that the necessity of replacement of the faulty elements is eliminated. Simulation is done on the linear antenna array constructed of individual isotropic elements separated by identical inter-element spacing and the results obtained from the simulation depict the effectiveness of the proposed method. This method can also be extended to other array geometries. [ABSTRACT FROM AUTHOR]

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. [Copyright &y& Elsevier]

Design of thinned elliptical antenna arrays of uniformly excited isotropic antennas using particle swarm optimization (PSO), is reported. Thinned arrays can generate directive beam with minimum side lobe level (SLL) without degrading the performance of fully populated antenna arrays significantly. Thinning of elliptical antenna arrays using PSO are optimized with different values of eccentricity and variation of side lobe level with eccentricity of thinned antenna array is reported. Using optimization method, it is found that by changing eccentricity of elliptic arrangement of an antenna array, reduced side lobe levels can be obtained. Thinning of concentric elliptical array, using PSO, is also reported in this paper. [ABSTRACT FROM AUTHOR]

Modifications in the velocity calculation of the particle swarm optimization (PSO) algorithm are proposed. The suggested modifications aim to arrive at a faster, more straightforward and still robust search procedure as compared to the conventional method. Two main factors, i.e., personal best influence and initial velocity values, are evaluated. It is shown that in problems with wide-range parameters, the effect of personal best locations is intrinsically encompassed by that of global best locations, thereby allowing for further simplification of the PSO algorithm by eliminating the factor which accounts for the personal best solutions in the velocity calculation. This simplification expedites the convergence procedure in real PSO. It is also shown that the initial velocity values can be modified to enhance the performance in terms of achieving better solution when compared with the existing algorithms, particularly in binary PSO. In order to validate the viability of the proposed procedure, the performances of the real-number and binary PSO algorithms with different velocity calculations are assessed in 1000-run sets, and pros and cons are studied. In particular, the performance of the proposed algorithm, when used to design software defined thinned array antennas, is shown to be superior to those of the existing algorithms. [ABSTRACT FROM AUTHOR]