Design of a Circularly Polarized Galileo E6-Band Textile Antenna by Dedicated Multiobjective Constrained Pareto Optimization

Abstract

Designing textile antennas for real-life applications requires a design strategy that is able to produce antennas that are optimized over a wide bandwidth for often conflicting characteristics, such as impedance matching, axial ratio, efficiency, and gain, and, moreover, that is able to account for the variations that apply for the characteristics of the unconventional materials used in smart textile systems. In this paper, such a strategy, incorporating a multiobjective constrained Pareto optimization, is presented and applied to the design of a Galileo E6-band antenna with optimal return loss and wide-band axial ratio characteristics. Subsequently, different prototypes of the optimized antenna are fabricated and measured to validate the proposed design strategy.

Constrained multi‐objective antenna design optimization using surrogates

“…Engineering optimization problems, such as the design of electronic filters and antennae, involve computationally expensive electromagnetic field simulations. Using multiobjective evolutionary algorithms (MOEAs) and genetic algorithms [1][2][3][4][5][6] is not desirable, since they typically require a large number of objective function evaluations during the optimization process.…”