Generalised shape-preserving response prediction for accurate modelling of microwave structures

A generalised shape-preserving response prediction (generalised SPRP or GSPRP) methodology for low-cost and accurate modelling of microwave structures is discussed. The GSPRP method predicts the response of a high-fidelity electromagnetic-simulated model (e.g. S-parameters against frequency) using sets of characteristic points and translation vectors obtained from underlying low-fidelity model responses. Unlike the original SPRP technique, which uses a limited number of training points at restricted locations, GSPSP can utilise an arbitrary number of training points, which are handled through Kriging interpolation applied to model a set of characteristic points corresponding to the entire training set. This increases the flexibility of SPRP and allows us to improve the modelling accuracy if more training points are available. At the same time, the GSPRP inherits the main advantage of SPRP: good prediction accuracy without using a large amount of data, which is in contrast to conventional approximation techniques. This is ensured as the locations of the characteristic points are easy to model. The proposed technique is demonstrated through a comprehensive numerical study as well as comparison with other modelling techniques. Application examples are also given.