Characterisation by Gaussian processes of finite substrate size effects on gain patterns of microstrip antennas

Abstract

A procedure is presented for characterising the effects of varying finite substrate/ground plane size on the gain properties of microstrip antennas by means of Gaussian process regression (GPR). Two kinds of microstrip antenna were considered, namely a probe-fed patch antenna on both thin and thick dielectric substrates, and an L-probe-fed patch on a thick air substrate. CST Microwave Studio was used to generate training and test data for the GPR models. Frontal E and Hplane gain patterns could be predicted with normalised root-mean-square errors (RMSEs) of <1.8% for the thin-substrate probe-fed patch and the L-probe-fed patch; for the thick-substrate probe-fed patch, RMSEs were 2.1 and 2.8% for the two principal plane gain patterns, respectively. Furthermore, the GPR models could predict patterns at least two orders of magnitude faster than it took to obtain them via direct simulation in CST. Such models are expected to be useful in CAD-based environments for rapidly obtaining estimates of substrate/ground-plane size effects on gain characteristics in lieu of time-consuming full-wave simulations.