Abstract

Managing sidelobe levels (SLLs) in metasurface-driven beam-steering antennas poses a significant challenge due to intrinsic factors leading to grating lobes. Our proposed method employs an equivalent model to efficiently optimize large periodic metasurfaces. This model predicts complete metasurface performance, accounting for mutual coupling between patches. We introduce an evolutionary optimization algorithm based on the cross-entropy (CE) method to enhance PGM-based beam-steering antennas and suppress sidelobes. Two strategies are employed: the first is to optimize the patch dimensions for a sidelobe-free pattern, and the second is to maintain the PGM dimensions while optimizing the feed array amplitudes. Both strategies effectively suppress sidelobes, offering insights into the CE method’s applicability and effectiveness for CPU-intensive electromagnetic optimization challenges. The proposed CE method variant retains its simplicity while improving monitoring capabilities, addressing this limitation. Smaller generations yield better improvements per evaluation. The uniqueness of the proposed optimization strategy lies in its utilization of an equivalent 1D metasurface model for optimization that not only considers the mutual coupling between identical unit cells along the y-direction within a complete metasurface but also takes into account the distinct cells along the x-direction. Moreover, the 1D metasurface model incorporates the influence of edge effects along the x-direction.

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