Synthesis of Modular Contiguously Clustered Linear Arrays Through a Sparseness-Regularized Solver

An innovative methodology for the design of modular and contiguously-clustered linear arrays is proposed. The approach formulates the subarraying problem as a pattern matching one in which elementary modules taken from a user-defined dictionary are combined to synthesize the final antenna layout. By recasting such a synthesis problem within the compressive sensing framework, an efficient solver is used to determine the array architecture starting from the a priori specification of the features (e.g., the length) of the admissible subarrays. A set of representative numerical experiments is discussed to assess the advantages and drawbacks of the proposed algorithm also in comparison with some state-of-the-art methods.