Abstract
This paper presents an efficient technique of microstrip magnetic dipoles design that explores the physics ruling the antenna behavior not restricting to parametric analyses in a full-wave simulation software. The proposed approach makes use of the cavity model whose parameters are progressively enhanced by using full-wave electromagnetic simulation data in a feedback scheme. A curve fitting problem is established to evaluate the mentioned parameters at each iteration. To exemplify the developed technique, a microstrip magnetic dipole operating at 2.44 GHz (ISM band) was synthesized and its prototype was manufactured and tested in an anechoic chamber. The design was ready in less than one hour and only three full-wave simulations were required. A good agreement between theoretical predictions and experimental results was also observed.
Highlights
Microstrip magnetic dipoles are a variation of probe-fed rectangular microstrip antennas in which three of the patch edges are shorted to the ground plane by conducting walls
In this paper, an efficient technique able to assist the design of microstrip magnetic dipoles and that explores the physics behind the dipoles behavior is proposed
It employs a surrogate model that is an extension of the cavity model for a rectangular patch antenna with three metallic vertical walls
Summary
Microstrip magnetic dipoles are a variation of probe-fed rectangular microstrip antennas in which three of the patch edges are shorted to the ground plane by conducting walls. As a comparison, [11] employed a physics-based surrogate consisting of an adapted version of the well-known transmission-line model to perform the design of electrically thick differentially driven probe-fed microstrip antennas It required only three full-wave simulations to finish the design of the radiator presented in that paper. Reference [12] in turn uses the array factor of an array of isotropic point sources to define a surrogate model that guides the design of linear microstrip antennas arrays By using this technique, those microstrip arrays spend only three full-wave simulations with fine discretization mesh to be synthesized. Some papers propose the use of artificial neural networks [13] or polynomial regression [14] to assist in the design of printed antennas Those techniques have the disadvantage of requiring training data points for the building of their models, whose assembly is usually time-consuming.
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