An alternative electromagnetic (EM) optimisation technique for the optimal design of frequency selective surfaces (FSSs) with fractal motifs is described. Based on computational intelligence tools, the proposed technique overcomes the high computational cost associated with FSS parametric full‐wave analysis. In an application example, a fast and accurate multilayer perceptrons model of a FSS band‐stop spatial filter with a Vicsek fractal motif is developed. This neural network model is used for repetitive cost function computations in population‐based search algorithm simulations. A bees algorithm, continuous genetic algorithm and particle swarm optimisation are used for FSS optimisation with specific resonant frequency and bandwidth. The performance of these algorithms is compared in terms of numerical convergence. Consistent results are presented for a second‐pass of designed FSS prototype with Vicsek fractal elements.

This work presents a fractal design methodology for frequency selective surfaces (FSSs) with Peano pre‐fractal patch elements. The proposed FSS structures are composed of periodic arrays of metallic patches printed on a single‐layer fibreglass dielectric. The shapes presented by pre‐fractal patches allow one to design compact FSSs that behave like dual‐polarised band‐stop spatial filters. On the other side, the space‐filling and self‐similarity properties of Peano fractals became possible various configurations for patch elements. An FSS parametric analysis is performed in terms of the fractal iteration‐number and cell‐size of pre‐fractal patches. To validate the used methodology four FSS prototypes are built and tested in the range from 1.0 to 13.5 GHz. Experimental characterisation of the FSS prototypes is accomplished through three different measurement setups with commercial horns and circular monopole microstrip antennas. Results show that the proposed FSS presents most of the desired features for spatial filters: compact design, multiband responses, dual‐polarisation, excellent angular stability and facility for reconfiguration.

This paper presents a design methodology for frequency selective surfaces (FSSs) using metallic patches with dissimilar Sierpinski fractal elements. The transmission properties of the spatial filters are investigated for FSS structures composed of two alternately integrated dissimilar Sierpinski fractal elements, corresponding to fractal levels = 1, 2, and 3. Two FSS prototypes are fabricated and measured in the range from 2 to 12 GHz to validate the proposed fractal designs. The FSSs with dissimilar Sierpinski fractal patch elements are printed on RT/Duroid 6202 high frequency laminate. The experimental characterization of the FSS prototypes is accomplished through two different measurement setups composed of commercial horns and elliptical monopole microstrip antennas. The obtained results confirm the compactness and multiband performance of the proposed FSS geometries, caused by the integration of dissimilar fractal element. In addition, the proposed FSSs exhibited frequency tuning ability on the multiband frequency responses. Agreement between simulated and measured results is reported.