Application of the Global Optimization Approaches To Planar Near-Field Antenna Phaseless Measurements

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F09%3APU80389" target="_blank" >RIV/00216305:26220/09:PU80389 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Application of the Global Optimization Approaches To Planar Near-Field Antenna Phaseless Measurements

Popis výsledku v původním jazyce

This paper deals with a method of the radiation pattern determination of the directional antennas. The method combining both the functional minimization method and the Fourier iterative algorithm is based on the phaseless near-field measurement on two plane surfaces. The method is used for a reconstruction of the phase distribution on the aperture of the measured antenna, and for the determination of the antenna radiation pattern, consequently. The binary genetic algorithm (BGA), the real-valued geneticalgorithm (RVGA), the particle swarm optimization (PSO) and differential evolutionary algorithm (DEA) were chosen for the global functional minimization. The paper is aimed to analyze the performance of the global optimizations (GOs) when solving the described problem, and to compare the GOs. GOs were exemined through datas achieved by measurement of the horn atenna and the parabola.

Název v anglickém jazyce

Application of the Global Optimization Approaches To Planar Near-Field Antenna Phaseless Measurements

Popis výsledku anglicky

This paper deals with a method of the radiation pattern determination of the directional antennas. The method combining both the functional minimization method and the Fourier iterative algorithm is based on the phaseless near-field measurement on two plane surfaces. The method is used for a reconstruction of the phase distribution on the aperture of the measured antenna, and for the determination of the antenna radiation pattern, consequently. The binary genetic algorithm (BGA), the real-valued geneticalgorithm (RVGA), the particle swarm optimization (PSO) and differential evolutionary algorithm (DEA) were chosen for the global functional minimization. The paper is aimed to analyze the performance of the global optimizations (GOs) when solving the described problem, and to compare the GOs. GOs were exemined through datas achieved by measurement of the horn atenna and the parabola.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Radioengineering

ISSN

1210-2512

e-ISSN

—

Svazek periodika

18

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

9

Strana od-do

—

Kód UT WoS článku

—

EID výsledku v databázi Scopus

—