Fast Multiobjective Optimization of Narrowband Antennas Using RSA Models and Design Space Reduction

Abstract

A computationally efficient technique for multiobjective design optimization of narrowband antennas is presented. In our approach, the corrected low-fidelity antenna model [obtained through coarse-discretization electromagnetic (EM) simulations] is enhanced using frequency scaling and response correction, sampled, and utilized to obtain a fast response surface approximation (RSA) antenna surrogate. The RSA model is constructed in the reduced design space. The initial set of Pareto-optimal designs is then utilized to confine the design space further by identifying designs that satisfy minimum requirements with respect to antenna reflection response. The updated RSA model set up in the confined space is subsequently optimized to yield the final Pareto set at the low computational cost.