An efficient and fast strategy to design and realize single layer Fourier phased metasurfaces for wideband radar cross section (RCS) reduction when illuminated by a circular polarization (CP) plane wave is proposed in this letter. The scattering phase (between 0 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> and 360 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> ) required at each unit cell of the proposed metasurfaces was computed using the Fourier phase formula in which the focal length ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</i> ) is inversely proportional to the phase distribution. Pancharatnam-Berry (PB) phase theory was applied with unit cells of subwavelength periodicity to further enhance the scattering and RCS reduction characteristics. The proposed wideband Fourier phased metasurface has a square shape and contains 30 × 30 PB unit cells with subwavelength periodicity of 5 mm ≈ 0.26λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">16GHz</sub> . Both simulation and measured results show that the proposed Fourier phased metasurfaces can achieve more than 10 dB of RCS reduction under normal incidence of CP plane wave regardless of the value of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</i> . Under oblique incidence, more than 10 dB of RCS reduction was maintained for incident angles up to 60°. In addition, the single-layer Fourier phased metasurface features wideband 10 dB RCS reduction bandwidth from 10 GHz to 24 GHz with a thickness of only 2 mm. This resulted in an 82.3% fractional bandwidth (FBW) of RCS reduction which is higher than other designs reported in the literature. The proposed design strategy provides a promising way to design and realize metasurfaces for wideband and stable RCS reduction performance without the need to use a computationally complex and/or time-consuming and slow running optimization algorithm.
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