Design and Optimization of an Ultrathin and Broadband Polarization-Insensitive Fractal FSS Using the Improved...

Area of Science:

• Electromagnetics
• Materials Science
• Optimization Algorithms

Background:

• Frequency-selective surfaces (FSS) are crucial for controlling electromagnetic wave propagation.
• Traditional FSS design methods can be computationally intensive and time-consuming.
• Fractal geometries offer unique properties for FSS applications.

Purpose of the Study:

• To propose a novel and efficient optimization method for designing frequency-selective surfaces (FSS).
• To develop advanced fractal FSS structures with wideband and stable performance.
• To accelerate the FSS design process by integrating curve-fitting with optimization algorithms.

Main Methods:

• A hybrid optimization approach combining curve-fitting and an improved bacterial foraging optimization (IBFO) algorithm.
• Design of novel Koch curve-like and Minkowski fractal islands FSS structures.
• Utilizing curve-fitting for fitness evaluation in the IBFO algorithm to reduce electromagnetic simulations.
• Comparison of IBFO with classical BFO, BSO, and ABC algorithms.

Main Results:

• The proposed IBFO algorithm demonstrates superior performance compared to other optimization techniques.
• Fabricated fractal FSS achieved a wide fractional bandwidth of 91.7% from 3.41 to 9.19 GHz (S, C, and X-bands).
• The FSS structure is exceptionally thin (0.025λ to 0.067λ).
• Stable performance was observed for both TE and TM polarizations at oblique incidence angles up to 45°.

Conclusions:

• The proposed curve-fitting and IBFO method significantly speeds up the FSS design process.
• The novel fractal FSS designs exhibit excellent wideband characteristics and stable performance.
• This approach offers a promising solution for efficient design of advanced FSS devices.