A review on optimization of antenna array by evolutionary optimization techniques

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
D.D. Devisasi Kala ◽  
D. Thiripura Sundari
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Optimization Algorithm ◽  
Firefly Algorithm ◽  
Side Lobe ◽  
Optimization Techniques ◽  
Swarm Optimization ◽  
Content Type ◽  
Gain Enhancement ◽  
Whale Optimization

PurposeOptimization involves changing the input parameters of a process that is experimented with different conditions to obtain the maximum or minimum result. Increasing interest is shown by antenna researchers in finding the optimum solution for designing complex antenna arrays which are possible by optimization techniques.Design/methodology/approachDesign of antenna array is a significant electro-magnetic problem of optimization in the current era. The philosophy of optimization is to find the best solution among several available alternatives. In an antenna array, energy is wasted due to side lobe levels which can be reduced by various optimization techniques. Currently, developing optimization techniques applicable for various types of antenna arrays is focused on by researchers.FindingsIn the paper, different optimization algorithms for reducing the side lobe level of the antenna array are presented. Specifically, genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), cuckoo search algorithm (CSA), invasive weed optimization (IWO), whale optimization algorithm (WOA), fruitfly optimization algorithm (FOA), firefly algorithm (FA), cat swarm optimization (CSO), dragonfly algorithm (DA), enhanced firefly algorithm (EFA) and bat flower pollinator (BFP) are the most popular optimization techniques. Various metrics such as gain enhancement, reduction of side lobe, speed of convergence and the directivity of these algorithms are discussed. Faster convergence is provided by the GA which is used for genetic operator randomization. GA provides improved efficiency of computation with the extreme optimal result as well as outperforming other algorithms of optimization in finding the best solution.Originality/valueThe originality of the paper includes a study that reveals the usage of the different antennas and their importance in various applications.

scholarly journals Null Steering in Failed Antenna Arrays

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Om Prakash Acharya ◽  
Amalendu Patnaik ◽  
Sachendra N. Sinha
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Correction Procedure ◽  
Swarm Optimization ◽  
Array Pattern ◽  
Null Steering ◽  
Simulation Results ◽  
Pattern Simulation

Antenna array pattern nulling is desirable in order to suppress the interfering signals. But in large antenna arrays, there is always a possibility of failure of some elements, which may degrade the radiation pattern with an increase in side lobe level (SLL) and removal of the nulls from desired position. In this paper a correction procedure is introduced based on Particle Swarm Optimization (PSO) which maintains the nulling performance of the failed antenna array. Considering the faulty elements as nonradiating elements, PSO reoptimizes the weights of the remaining radiating elements to reshape the pattern. Simulation results for a Chebyshev array with imposed single, multiple, and broad nulls with failed antenna array are presented.

An improved peak side lobe reduction method for linear array antenna for military applications

2021 ◽  
Vol 14 (2) ◽  
pp. 186-198
Author(s):  
Ravi Tej D ◽  
Sri Kavya Ch K ◽  
Sarat K. Kotamraju
Keyword(s):  
Energy Efficiency ◽  
Antenna Array ◽  
Antenna Arrays ◽  
Spectral Efficiency ◽  
Communication System ◽  
Communication Systems ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Fill Rate ◽  
Content Type

PurposeThe purpose of this paper is to improve energy efficiency and further reduction of side lobe level the algorithm proposed is firework algorithm. In this paper, roused by the eminent swarm conduct of firecrackers, a novel multitude insight calculation called fireworks algorithm (FA) is proposed for work enhancement. The FA is introduced and actualized by mimicking the blast procedure of firecrackers. In the FA, two blast (search) forms are utilized and systems for keeping decent variety of sparkles are likewise all around planned. To approve the presentation of the proposed FA, correlation tests were led on nine benchmark test capacities among the FA, the standard PSO (SPSO) and the clonal PSO (CPSO).Design/methodology/approachThe antenna arrays are used to improve the capacity and spectral efficiency of wireless communication system. The latest communication systems use the antenna array technology to improve the spectral efficiency, fill rate and the energy efficiency of the communication system can be enhanced. One of the most important properties of antenna array is beam pattern. A directional main lobe with low side lobe level (SLL) of the beam pattern will reduce the interference and enhance the quality of communication. The classical methods for reducing the side lobe level are differential evolution algorithm and PSO algorithm. In this paper, roused by the eminent swarm conduct of firecrackers, a novel multitude insight calculation called fireworks algorithm (FA) is proposed for work enhancement. The FA is introduced and actualized by mimicking the blast procedure of firecrackers. In the FA, two blast (search) forms are utilized and systems for keeping decent variety of sparkles are likewise all around planned. To approve the presentation of the proposed FA, correlation tests were led on nine benchmark test capacities among the FA, the standard PSO (SPSO) and the clonal PSO (CPSO). It is demonstrated that the FA plainly beats the SPSO and the CPSO in both enhancement exactness and combination speed. The results convey that the side lobe level is reduced to −34.78dB and fill rate is increased to 78.53.FindingsSamples including 16-element LAAs are conducted to verify the optimization performances of the SLL reductions. Simulation results show that the SLLs can be effectively reduced by FA. Moreover, compared with other benchmark algorithms, fireworks has a better performance in terms of the accuracy, the convergence rate and the stability.Research limitations/implicationsWith the use of algorithms radiation is prone to noise one way or other. Even with any optimizations we cannot expect radiation to be ideal. Power dissipation or electro magnetic interference is bound to happen, but the use of optimization algorithms tries to reduce them to the extent that is possible.Practical implications16-element linear antenna array is available with latest versions of Matlab.Social implicationsThe latest technologies and emerging developments in the field of communication and with exponential growth in users the capacity of communication system has bottlenecks. The antenna arrays are used to improve the capacity and spectral efficiency of wireless communication system. The latest communication systems use the antenna array technology which is to improve the spectral efficiency, fill rate and the energy efficiency of the communication system can be enhanced.Originality/valueBy using FA, the fill rate is increased to 78.53 and the side lobe level is reduced to 35dB, when compared with the bench mark algorithms.

Minimizing sidelobe levels and facilitating null placements of nonlinear antenna arrays using an improved particle swarm optimization method

2013 ◽  
Vol 33 (1/2) ◽  
pp. 65-73 ◽  
Author(s):  
Huijun Deng ◽  
Xue Li ◽  
Libao Sun ◽  
Shiyou Yang
Keyword(s):  
Particle Swarm Optimization ◽  
Antenna Array ◽  
Antenna Arrays ◽  
Particle Swarm ◽  
Optimization Method ◽  
Entropy Method ◽  
Swarm Optimization ◽  
Content Type ◽  
Cross Entropy Method ◽  
Improved Pso

Purpose – The aim of this paper is to explore the potential of particle swarm optimization (PSO) methods for minimizing the sidelobe levels (SLL) and placing null at arbitrary angles of a nonlinear antenna array. Design/methodology/approach – An improved PSO algorithm is designed. Findings – The improved PSO method is an efficient and robust global optimizer for minimizing the SLL and placing null at arbitrary angles of a nonlinear antenna array. Originality/value – Some improvements, such as the design of some new formulae for both position and velocity updating, the introduction of an age variable, and the devise of an intensification searches using the cross entropy method, are proposed.

Optimum design of linear and circular antenna arrays using equilibrium optimization algorithm

2021 ◽  
pp. 1-12
Author(s):  
Ali Durmus ◽  
Rifat Kurban
Keyword(s):  
Antenna Array ◽  
Radiation Pattern ◽  
Antenna Arrays ◽  
Optimization Algorithm ◽  
Communication Systems ◽  
Control Volume ◽  
Optimization Technique ◽  
Beam Width ◽  
Side Lobe ◽  
Side Lobe Level

Abstract In this paper, equilibrium optimization algorithm (EOA), which is a novel optimization algorithm, is applied to synthesize symmetrical linear antenna array and non-uniform circular antenna array (CAA). The main purpose of antenna array synthesis is to achieve a radiation pattern with low maximum side lobe level (MSL) and narrow half-power beam width (HPBW) in far-field. The low MSL here is an important parameter to reduce interference from other communication systems operating in the same frequency band. A narrow HPBW is needed to achieve high directionality in antenna radiation patterns. Entering the literature as a novel optimization technique, EOA optimally determined the amplitude and position values of the array elements to obtain a radiation pattern with a low MSL and narrow HPBW. The EOA is inspired by models of the control volume mass balance used to predict equilibrium as well as dynamic states. To demonstrate the flexibility and performance of the proposed algorithm, 10-element, 16-element and 24-element linear arrays and eight-element, 10-element and 12-element CAAs are synthesized. The MSL and HPBW values of radiation pattern obtained with the EOA are very successful compared to the results of other optimization methods in the literature.

scholarly journals Cat Swarm Optimization Algorithm For Antenna Array Synthesis

2021 ◽  
Vol 12 (2) ◽  
pp. 1466-1474
Author(s):  
Nirmala Yerpula, Et. al.
Keyword(s):  
Antenna Array ◽  
Optimization Algorithm ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Swarm Optimization ◽  
Pillar Design ◽  
Mother Nature ◽  
Cat Swarm Optimization ◽  
Antenna Array Synthesis ◽  
Weighting Technique

Cat swarm optimization (CSO) is a developmental technique enlivened by the animals in Mother Nature for taking care of optimization issue. Short of what multi decade after CSO is proposed, it has been improved and applied in various fields by numerous scientists as of late. CSO is created by noticing the practices of cats, and made out of two sub-models, i.e., following mode and looking for mode, which model upon the practices of cats. The prerequisite of high directivity signal with extremely quick pillar guiding is preposterous by a solitary antenna. This imperative is aid by staged array antenna which is a mix of various little antennas that can create shaft with high directivity with quick electronic pillar guiding. The radiation example of an antenna array relies firmly upon the weighting technique and the math of the array. The issues related with pillar design causing high obstruction in communication which confine them use by and by. To beat these im-pediments, optimization innovation called Cat Swarm Optimization are applied in mix with the old style array blend strategies for staged array combination. An optimization issue is determined whose arrangement yields an ideal array for stifling impedance because of high side lobe level and grinding lobe. Results are introduced for ideal arrays of shifting array calculation, with various number of antenna components, and for distinct beamwidths and scan angles.

scholarly journals 3D Antenna Array Design using Firefly Optimization Algorithm

2019 ◽  
Vol 4 (2) ◽  
pp. 61-70
Author(s):  
Abdelmadjid RECIOUI ◽  
Youcef GRAINAT
Keyword(s):  
Global Optimization ◽  
Antenna Array ◽  
Antenna Arrays ◽  
Optimization Algorithm ◽  
Optimization Technique ◽  
Optimization Method ◽  
Side Lobe ◽  
Population Based ◽  
Synthesis Process ◽  
Side Lobe Level

The design of antenna arrays in a 3D geometry is presented in this Chapter. The decision variables considered for this synthesis problem are the array element amplitude excitations. The objective is to design an array which ensures minimum sidelobe level and a high directivity. The synthesis process is carried out using a nature-inspired global optimization technique. The optimization method based on the reaction of a firefly to the light of other fireflies is known as Firefly Algorithm (FA). It is a population-based iterative heuristic global optimization algorithm technique, developed by Xin-She Yang, for multi-dimensional and multi-modal problems. Simulation results for an antenna array with isotropic elements show that side lobe level is significantly reduced in non-uniform case. Besides, the directivity is not worse than that of the uniform one.

scholarly journals Antenna Array Weight Synthesis for Low Side Lobe Levels using Window Functions

2019 ◽  
Vol 9 (1) ◽  
pp. 3074-3081
Keyword(s):  
Antenna Array ◽  
Radiation Pattern ◽  
Antenna Arrays ◽  
Side Lobe ◽  
Optimization Techniques ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Window Functions ◽  
Linear Antenna Arrays ◽  
Array Weight

A lot of research is being carried out to reduce side lobe levels (SSLs) in the radiation pattern of antenna arrays. A number of novel optimization techniques have been developed over the years and adapted for this purpose. In this paper, a number of window functions are applied to suppress the maximum side lobe level (MSLL) in linear antenna arrays. The window functions Bartlett, Taylor, Hanning, Barthann, Hamming, Gaussian, Blackman, Chebyshev, Blackman-Harris and Kaiser are considered in the simulation. The optimized pattern for a 10 element linear antenna array and corresponding normalized window tappers for every window are presented. Finally the efficiency of all windows is compared in terms of their computed parameters.

scholarly journals The optimal synthesis of scanned linear antenna arrays

2020 ◽  
Vol 10 (2) ◽  
pp. 1477
Author(s):  
Anas A. Amaireh ◽  
Asem S. Al-Zoubi ◽  
Nihad I. Dib
Keyword(s):  
Antenna Arrays ◽  
Firefly Algorithm ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Symbiotic Organisms Search ◽  
Optimization Parameters ◽  
Antlion Optimization ◽  
Symbiotic Organisms ◽  
Linear Antenna Arrays

In this paper, symmetric scanned linear antenna arrays are synthesized, in order to minimize the side lobe level of the radiation pattern. The feeding current amplitudes are considered as the optimization parameters. Newly proposed optimization algorithms are presented to achieve our target; Antlion Optimization (ALO) and a new hybrid algorithm. Three different examples are illustrated in this paper; 20, 26 and 30 elements scanned linear antenna array. The obtained results prove the effectiveness and the ability of the proposed algorithms to outperform and compete other algorithms like Symbiotic Organisms Search (SOS) and Firefly Algorithm (FA).

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