Abstract
Maintaining small size has become an important consideration in the design of contemporary antenna structures. In the case of broadband circularly polarized (CP) antennas, miniaturization is a challenging process due to the necessity of simultaneous handling of electrical and field properties (reflection, axial ratio, gain), as well as ensuring sufficient frequency range of operation, especially at the lower edge of the antenna bandwidth. An additional difficulty is that-for the sake of reliability-the design process has to be based on full-wave electromagnetic simulation tools. This is a computationally expensive endeavor because rendering the minimum-size design under the assumed constraints concerning the operating frequencies requires rigorous numerical optimization, which entails massive evaluations of the structure at hand. This paper describes an algorithmic framework for efficient identification of broadband CP antenna designs that realize the best possible trade-offs (Pareto set) between the antenna size and its operating bandwidth. The designs are generated sequentially by solving local optimization tasks targeting explicit reduction of the antenna footprint with implicit constraints imposed on the reflection and axial ratio characteristics. The data accumulated during the previous iterations is employed to yield good initial points for further stages by means of inverse surrogates and extrapolation. Low cost of the process is ensured by sparse sensitivity updates within the trust-region gradient-based algorithm being the main optimization engine. The proposed methodology is demonstrated using three examples of wide-slot CP structures with the trade-off designs representing broad ranges of achievable antenna sizes and operating bandwidth. The framework can be used to assess the antenna suitability for particular application areas as well to conclusively compare alternative CP geometries from the point of view of achievable miniaturization rate and capability of fulfilling given performance requirements.