An Innovative Computational Approach Based on a Particle Swarm Strategy for Adaptive Phased-Arrays Control

In this paper a new approach to the control of phased arrays is presented and assessed. Starting from the adaptive array theory, a particle swarm strategy is used to tune the phase coefficients of the array in order to adaptively minimize/avoid the effects of interfering signals at the receiver. To show the effectiveness of the proposed approach, a selected set of numerical examples, concerned with linear as well as planar arrays, is presented. Furthermore, to evaluate the advantages of the particle swarm optimizer (PSO)-based strategy over state-of-art methods, a comparative study is carried out by analyzing the performance of the method in terms of both the signal-to-interference-plus-noise-ratio and resulting beam pattern. The achieved results, even though preliminary, seem to confirm that the PSO-based approach satisfactorily works and it generally outperforms previously proposed/state-of-art phase-only adaptive control strategies