Elliptical Antenna Array Synthesis using Evolutionary Computing Tools

Elliptical antenna arrays (EAA) are capable of steering the principal beam to any direction, and they possess ease in realization as they need not be perfectly circular in shape. Novel evolutionary computing tools (ECT) can be used to design EAA without much complexity. In this paper, the design of EAA is transformed and addressed as an optimization problem. Unlike previous efforts, the eccentricity of the ellipse is included along with the design parameters like amplitude and angular position in the optimization process. This enhances the search capability and provides a better solution in terms of lower sidelobe level (SLL) for a fixed uniform first null beamwidth (FNBW). The search capability within the solution space is directly proportional to the number of search parameters. In this work, eccentricity is the additional search parameter that enhances the degree of freedom. Accordingly, it is optimized along with other design parameters rather than taking some discrete values, likewise in the parametric analysis as performed in the relevant available literature. Both the flower pollination algorithm and accelerated particle swarm optimization algorithm are used for synthesizing the EAA with the objective of SLL suppression and fixed uniform FNBW. It is evident from the results that the improvement in the SLL suppression is due to the inclusion of the additional design parameter.

Automated summary

The study used evolutionary computing tools to design elliptical antenna arrays by optimizing the eccentricity of the ellipse and other design parameters, enhancing search capability and obtaining a better solution under fixed beamwidth. Including eccentricity as an additional search parameter improves freedom and optimization results.