A Novel Encoding Strategy of Enhanced Broadband and Absorption Conformable Metamaterial for MW Applications

Analog metamaterials (MMs) manipulate their effective medium parameters with difficulty, when their geometric architecture is composed of hybrid compositions. However, genetic algorithms, calculation-analog search algorithms that seek for optimal solutions, can be applied to artificial metamaterial-architecture construction. This paper proposes a novel encoding strategy for metamaterial architecture construction that utilizes multi-parameter extremum-seeking optimization. The binary encoding and decoding of the geometric-layer thickness enables the form's final dimension to be based on the objective fitness function. The genetic algorithm iteratively optimizes the initial geometrical dielectric-layer thicknesses. Then, combining the initial optimized parameter with the composite-metal multi-loops' spatial distribution, the final metamaterials were analyzed using numerical analysis software. Based on a co-simulation disposition, the proposed metamaterial exhibits 2.5-GHz broadband features with over 80% physical absorption of spatial waves. The proposed metamaterial simultaneously presents low radar cross-sections, wide polarization insensitivity, and dynamical flexibility. Moreover, the proposed metamaterial, when loaded onto a reference antenna, exhibited good real application capability in radar cross-section reduction for physical passive-equipment invisibility. The numerical-simulation and experimental results of the MM's absorption and flexibility properties showed good agreement, suggesting the advantage of genetic-algorithm optimization co-simulated with numerical-analysis software for metamaterial architecture construction. It shows good potential application for complicated spatial-geometry formations.