Accelerated Re-Design of Antenna Structures Using Sensitivity-Based Inverse Surrogates

Abstract

The paper proposes a novel framework for accelerated redesign (dimension scaling) of antenna structures using inverse surrogates. The major contribution of the work is a sensitivity-based model identification procedure, which permits a significant reduction of the number of reference designs required to render the surrogate. Rigorous formulation of the approach is supplemented by its comprehensive numerical validation using a triple-band uniplanar dipole antenna and a dual-band monopole antenna redesigned with respect to operating frequencies as well as the substrate parameters (thickness and dielectric permittivity). It is demonstrated that-for the considered test cases-the reliable inverse model can be set up using a significantly smaller (by a factor of three) number of reference points as compared to the original version of the method, whereas the dimension scaling process itself requires up to four EM simulations of the antenna structure. INDEX TERMS Antenna design, dimension scaling, inverse modeling, simulation-driven design, response sensitivities.

On Computationally-Efficient Reference Design Acquisition for Reduced-Cost Constrained Modeling and Re-Design of Compact Microwave Passives

“…In practice, it often has to be aided by engineering experience already at the stage of finding a sufficiently good initial design, which is routinely performed through interactive parametric studies. At this point, it has to be reiterated that apart from the aforementioned performance-driven modelling methods, the database design sets are also crucial for rendering inverse surrogates (see, e.g., [63]), which allow for direct estimation of the optimum parameter vectors corresponding to given target values of the performance figures. The advantages come from a typically low-dimensionality of the objective space as compared to the (geometry) parameter space of most practical microwave components.…”