Radiation Pattern Synthesis of the Coupled almost Periodic Antenna Arrays Using an Artificial Neural Network Model

Abstract

This paper proposes radiation pattern synthesis of almost periodic antenna arrays including mutual coupling effects (extracted by Floquet analysis according to our previous work), which in principal has high directivity and a large bandwidth. For modeling the given structures, the moment method combined with the generalized equivalent circuit (MoM-GEC) is proposed. The artificial neural network (ANN), as a powerful computational model, has been successfully applied to antenna array pattern synthesis. Our results showed that multilayer feedforward neural networks are rugged and can successfully and efficiently resolve various distinctive, complex almost periodic antenna patterns (with different source amplitudes) (in particular, both periodic and randomly aperiodic structures are taken into account). An ANN is capable of quickly producing the synthesis results using generalization with the early stopping (ES) method. Significant advantages in speed and memory consumption are achieved by using this method to improve the generalization (called early stopping). To justify this work, several examples are shown and discussed.