Cost-efficient dual-stage Gaussian process modeling of antennas

Cost-efficient antenna modeling exploiting variable-fidelity EM simulations is proposed. Our approach is based on a new dual-stage Gaussian process regression method and allows for significant (by 80% or more) reduction of the computational effort necessary to set up the training data sets for the high-fidelity models with insignificant loss in predictive power. The proposed method is using a broadband slot antenna example. Application for design optimization is also discussed.