Synthesis of large sparse linear arrays by Bayesian Compressive Sensing

An innovative methodology for the synthesis of sparse linear arrays with prescribed pattern features is numerically analyzed when dealing with large aperture layouts. The technique is based on a probabilistic formulation of the synthesis problem which is solved through a Bayesian Compressive Sensing (BCS) technique. A set of numerical experiments are presented to assess the features and potentialities of the BCS design approach when layouts comprising several hundred elements are at hand.