Space mapping technology with applications in EM-based device modeling and statistical design

Abstract

The Space Mapping concept intelligently links companion “coarse” and “fine” engineering models of different complexities, e.g., full-wave electromagnetic (EM) simulations and empirical circuit-theory based models. A comprehensive framework to engineering device modeling which we call Generalized Space Mapping (GSM) has been developed. GSM is a tableau-based approach. It permits many different practical implementations. As a result the accuracy of available empirical models of microwave devices can be significantly enhanced in selected regions of interest in the parameter space. We present two fundamental illustrations: a basic Space Mapping Super Model (SMSM) which maps designable device parameters and a Frequency-Space Mapping Super Model (FSMSM) which also maps the frequency variable. The SMSM and FSMSM concepts have been verified on several modeling problems, typically utilizing a few relevant full-wave EM simulations. We present several microstrip examples, yielding remarkable modeling improvement. We consider the GSM technique to be very easy to implement. It has been reported to be very useful in the RF industry for development of new library models involving commercial software such as Agilent Momentum and ADS. Accurate yield optimization and statistical analysis of microwave components are crucial for manufacturability-driven designs in a time-to-market development environment. Yield optimization requires intensive simulations to cover the entire statistic of possible outputs of a given manufacturing process. An efficient procedure to realize EM-based yield optimization and statistical analysis of microwave structures using space mapping based neuromodels will be presented. Several practical microwave components illustrate our technique using commercial EM simulators.