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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization

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Reflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths,… Click to show full abstract

Reflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using 3D printing technology. Regardless of the implementation details, a practical bottleneck of RA design is the necessity of independent adjustment of a large number of unit cells, which has to be carried out using full-wave electromagnetic (EM) simulation models to ensure reliability. The associated computational costs are extraordinary. A practical workaround is the incorporation of surrogate modeling methods; however, a construction of accurate metamodel requires a large number of training data samples. This letter introduces an alternative RA design approach, where the unit cells are adjusted using an inverse surrogate model established with a small number of anchor points, pre-optimized for the reference reflection phases. To ensure solution uniqueness, the anchor point optimization involves regularization, here, based on the minimum-volume condition for the unit cell. The presented approach reduces the computational cost of RA design to a few dozens of EM analyses of the cell. Several demonstration examples are provided, along with an experimental validation of the selected RA realization.

Keywords: rapid design; regularization; surrogate modeling; inverse surrogate; design; surrogate

Journal Title: IEEE Access
Year Published: 2023

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