Abstract

The observed growth in the complexity of modern antenna topologies fostered a widespread employment of numerical optimization methods as the primary tools for final adjustment of the system parameters. This is mainly caused by insufficiency of traditional design closure approaches, largely based on parameter sweeping. Reliable evaluation of complex antenna structures requires full-wave electromagnetic (EM) analysis. Yet, EM-driven parametric optimization is, more often than not, extremely costly, especially when global search is involved, e.g., performed with population-based metaheuristic algorithms. Over the years, numerous methods of lowering these expenditures have been proposed. Among these, the methods exploiting variable-fidelity simulations started gaining certain popularity. Still, such frameworks are predominantly restricted to two levels of fidelity, referred to as coarse and fine models. This paper introduces a reduced-cost trust-region gradient-based algorithm involving variable-resolution simulations, in which the fidelity of EM analysis is selected from a continuous spectrum of admissible levels. The algorithm is launched with the coarsest discretization level of the antenna under design. As the optimization process converges, for reliability reasons, the model fidelity is increased to reach the highest level at the final stage. The proposed algorithm allows for a significant reduction of the computational cost (up to sixty percent with respect to the reference trust-region algorithm) without compromising the design quality, which is corroborated by thorough numerical experiments involving four broadband antenna structures.

Citations

Authors (3)