Design of frequency-selective radomes using parallel Particle Swarm Optimisation

Particle Swarm Optimisation (PSO) is very much in the focus of interest inside the electromagnetics community at present. PSO developed by Kennedy and Eberhart [1] while trying to model the swarm behaviour of bees has surprisingly revealed interesting capabilities as an optimiser in general and recently in the area of EM- optimisation. Particularly the aspect of designing Frequency Selective Surfaces (FSS) as part of a radome is quite difficult to handle due to the inherent multi-modal and multi-dimensional nature of this kind of problem. In order to attack such defiances Genetic Algorithms (GA) have been used in the past in different implementations and versions like GA, parallel GA, Micro-GA and others. All these genetic algorithms feature a lot of tuneable system parameters affecting overall performance of the optimiser very much. This makes it rather difficult to find a suitable and / or optimal system parameter setting of the optimiser to be able to handle a given problem efficiently. PSO in contrast is equipped with an appealing small number of system parameters. This circumstance makes PSO very interesting for the development engineer in general.