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A novel technique to calculate the bandwidth of rectangular microstrip antenna elements with thick substrates

✍ Scribed by Mehmet Kara

Publisher
John Wiley and Sons
Year
1996
Tongue
English
Weight
589 KB
Volume
12
Category
Article
ISSN
0895-2477

No coin nor oath required. For personal study only.

✦ Synopsis

Existing methods to compute the bandwidth of probe-fed rectangular microstrip antenna elements are inaccurate for the range of substrate thicknesses considered for this research. When 0.0815h0 5 h (A0 is the free-space wacrelength and h is the substrate thickness) the effect of surface wacies is predominant and must be taken into account. A notiel closed-fom expression based on the cavity model and the exact Green's function for a grounded dielectric slab has been deueloped to compute the bandwidth of rectangular microstrip antenna elements, faking into account both the power radiated in space waves and the power radiated in surface waves. This method is original, simple, and easily included in a CAD system. The calculated results are in good agreement with H. Yamamoto, 2.

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ple reflections between the surface of the ground and the antenna. He has produced empirical antenna designs (Vee dipoles) similar to those discussed in this article. We would like to thank him for sharing with us his insight into this problem.

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Fonnulas based on transmission-line, cauiiy, and magnetic-wall models to determine the resonant fie quencks of u rectungular microstrip antenna element haue been studied and their ualidiiy assessed. Their cariations were experimentally r;erifred by analyzing u set of newly designed untennu elements

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Seueral formulas based on the cauity model and the transmission-line model are combined to produce closed-form expressions for calculating the input resonant resistance of probe-fed rectangular microstrip antenna elements with thick substrates. These apressions take into account the patch and substr

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In this work, a fuzzy hybrid approach FHA for the synthesis of rectangular microstrip antenna elements with thick substrates ( ) is presented. The FHA is based on a fuzzy genetic algorithm FGA and a controlled random search algorithm. The results obtained from the FHA are compared with the results o