Inteligência computacional aplicada na otimização de efeitos causados pelo uso de estruturas PBG em antenas de microfita

Abstract

The increasing demand for wireless technology in contemporary society requires the construction of integrated microwave circuits each time more sophisticated. In this sense, the planar microstrip antenna stands out because their small sizes and used in various applications, with emphasis on airplanes, satellites and mobile communication systems. In addition, recent researches shows the use of computing intelligence in telecommunications for analysis of new applications at microstrip antennas, as also the optimization of existing applications, searching for a better performance at the reception and / or signal transmission. In this context, this work has as objective get the radiation properties of microstrip antennas using the new models of Photonic Band Gap (PBG) structures based in meshes with periodic distributions and quasi-periodic printed on the substrate. In the practical procedures, prototypes of antennas were constructed that were used to obtain a database to feed the training process of an Artificial Neural Network (ANN), in order to obtain the resonance frequency of antennas. Finally, it was optimized the procedure for obtaining the project frequency and PBG structure required for a given operating frequency. According to the results, it can be concluded that it is possible to use an ANN in the optimization of a project of microstrip antenna with PBG substrate. The validation of the results provided by the ANN was based on building prototypes of the antennas, which showed good agreement between the simulated and measured values.