Optimizing the Gain and Directivity of a Microstrip Antenna with Metamaterial Structures by Using Artificial Neural Network Approach

被引：12
|
作者：
Sagik, Metin [1 ]
Altintas, Olcay [1 ]
Unal, Emin [1 ]
Ozdemir, Ersin [1 ]
Demirci, Mustafa [2 ]
Colak, Sule [3 ]
Karaaslan, Muharrem [1 ]
机构：
[1] Iskenderun Tech Univ, Fac Engn & Nat Sci, Dept Elect & Elect Engn, TR-31200 Iskenderun, Hatay, Turkey
[2] Iskenderun Tech Univ, Fac Engn & Nat Sci, Dept Civil Engn, TR-31200 Iskenderun, Hatay, Turkey
[3] Adana AlparslanTurkes Univ, TR-01140 Adana, Turkey
来源：
WIRELESS PERSONAL COMMUNICATIONS | 2021年 / 118卷 / 01期
关键词：
Microstrip antenna; Metamaterial; Gain; Directivity; Artificial neural network; FREQUENCY; DESIGN;
D O I：
10.1007/s11277-020-08004-8
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
The purpose of this study is to improve the gain and directivity of the microstrip patch antenna by means of metamaterial (MTM) structures. As it is known, antennas have power densities in a certain direction, and the radiation curves of the antennas are shaped by orienting them according to this power density. Based on this feature of the antennas, it is aimed to improve the gain and directivity of microstrip patch antennas with the most suitable structures thanks to metamaterial (MTM) structures. The MTM structures designed are interacted with the antenna. Then, the frequency, gain and directivity of the antenna are trained by the artificial neural network technique to estimate the most appropriate values. As a result, the gain and directivity of the antenna are improved by the interaction of microstrip patch antenna and MTM structures and the results are interpreted on the figures.
引用
收藏
页码：109 / 124
页数：16
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