Unequally spaced arrays synthesis using Self-adaptive Differential Evolution

In this paper we present uniformly excited unequally spaced linear-array synthesis with sidelobe suppression. We apply different evolutionary algorithms like Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) variants to position-only and position-phase synthesis. The DE algorithms include the common DE/rand/1/bin and the Self-adaptive strategies. The results on different problems show that the DE algorithms outperform the other algorithms in terms of finding best optima. The Self-adaptive DE produces similar or better results than the classical DE algorithm. The obtained results indicate the advantages of this approach.