On the modeling of non-stationary antenna responses by Gaussian processes
Jan Pieter Jacobs, Johan Joubert · 2017
This paper describes the modeling of the complex reflection coefficient S11of a meta-material antenna comprised of an etched microstrip dipole antenna radiating in the presence of a back reflector that is an artifical magnetic conductor (AMC). Both the real and imaginary components of the S parameter exhibit significant changes in rate of variation as a function of position along the frequency dimension of the input space. We show that Gaussian process regression — using a specially constructed composite covariance function that allows for a variable length-scale parameter along the frequency dimension — can succesfully model the components of S11. The latter model outperforms a GP model using a well-known standard covariance function from the (stationary) Matérn family.