Design of custom-made stacked patch antennas: A machine learning approach

Abstract

Machine learning approaches, viz. particle swarm optimization in conjunction with neural networks have been used to develop a user friendly tool to design custom-made stacked patch antennas in the entire X-Ku band for satellite communication application. The role of the neural network is to develop a black-box model to relate the frequencies of operation of the antenna with its dimensional parameters. This trained neural network was embedded in the loop of a particle swarm optimizer to decide the design dimensions required for specific user defined frequencies. The effectiveness and accuracy of the developed model are verified by simulations and experimental measurements. © 2012 Springer-Verlag.