Performance Evaluation of Population based Optimizers for the Synthesis of Linear Antenna Arrays

A. Arce, D.H. Covarrubias, and M.A. Panduro (Mexico)


Phase array, genetic algorithms, particle swarmoptimization.


Particle swarm optimization (PSO) is a high performance optimization technique recently introduced to solve synthesis problems. An important issue facing the user of PSO is the selection of parameters, as well as an efficient scheme to improve the optimization. This paper proposes the use of a global asynchronous PSO scheme in the design of linear antenna arrays. It is shown that PSO is more efficient than the well-known method of Genetic Algorithms (GAs), in terms of simplicity and computational burden. To illustrate the effectiveness of this PSO scheme applied to linear array synthesis, modelling and simulation examples including both GA and PSO algorithms are shown for the design problem analyzed.

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