In this work, methodologies for low-cost and reliable microwave modeling are presented using variable-fidelity response features. The two key components of our approach are: (i) a realization of the modeling process at the level of suitably selected feature points of the responses (e.g., S-parameters vs. frequency) of the structure at hand, and (ii) the exploitation of variable-fidelity EM simulation data, also for the response...

Electromagnetic (EM)-driven parameter adjustment has become imperative in the design of modern antennas. It is necessary because the initial designs rendered through topology evolution, parameter sweeping, or theoretical models, are often of poor quality and need to be improved to satisfy stringent performance requirements. Given multiple objectives, constraints, and a typically large number of geometry parameters, the design closure...

A framework for low-cost EM-driven design optimization of compact impedance matching transformers is presented. Our technique is based on a bottom-up design where design requirements for the transformer circuit are translated into specifications for its building blocks. These elementary cells are optimized using response features. Subsequently, the entire circuit is fine-tuned using local response surface approximation models and...

A technique for rapid EM-driven design optimization of compact microwave couplers is presented. Our approach exploits response features and adjoint sensitivities and allows for low-cost design closure both in terms of performance enhancement and structure miniaturization. It is demonstrated using a compact rat-race coupler working at 1 GHz and compared to adjoint-based gradient optimization.

Popularity of numerical optimization has been steadily on the rise in the design of modern antenna systems. Resorting to mathematically rigorous parameter tuning methods is a matter of practical necessity as interactive techniques (e.g., parameter sweeping) are no longer adequate when handling several performance figures over multi-dimensional parameter spaces. The most common design scenarios involve local tuning since decent...