Gain enhancement of an electrically small antenna array using metamaterials

2010 ◽  
Vol 102 (2) ◽  
pp. 345-351
Author(s):  
Bratin Ghosh ◽  
Susmita Ghosh
Keyword(s):  
Antenna Array ◽  
Electrically Small Antenna ◽  
Gain Enhancement ◽  
Small Antenna

Packaging technique for gain enhancement of electrically small antenna designed on gallium arsenide

2000 ◽  
Vol 36 (18) ◽  
pp. 1524 ◽  
Author(s):  
C.T.P. Song ◽  
P.S. Hall ◽  
H. Ghafouri-Shiraz ◽  
D. Wake
Keyword(s):  
Gallium Arsenide ◽  
Electrically Small Antenna ◽  
Gain Enhancement ◽  
Small Antenna ◽  
Packaging Technique

Demonstration of an Electrically Small Antenna Array for UHF Direction-of-Arrival Estimation

2013 ◽  
Vol 61 (3) ◽  
pp. 1371-1377 ◽  
Author(s):  
Matthew J. Slater ◽  
Christopher D. Schmitz ◽  
Michael David Anderson ◽  
Douglas L. Jones ◽  
Jennifer T. Bernhard
Keyword(s):  
Antenna Array ◽  
Direction Of Arrival ◽  
Direction Of Arrival Estimation ◽  
Electrically Small Antenna ◽  
Small Antenna

A novel metamaterial-inspired electrically small antenna fed by CPW

2008 ◽  
Author(s):  
Meng Li ◽  
Xian Qi Lin ◽  
Jessie Yao Chin ◽  
Ruopeng Liu ◽  
Tie Jun Cui
Keyword(s):  
Electrically Small Antenna ◽  
Small Antenna

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.

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