A Total-Variation Sparseness-Promoting Method for the Synthesis of Contiguously Clustered Linear Arrays

• Published in: IEEE transactions on antennas and propagation Vol. 67; no. 7; pp. 4589 - 4601
• Main Authors: Anselmi, Nicola, Gottardi, Giorgio, Oliveri, Giacomo, Massa, Andrea
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Antenna arrays; Clustered arrays; Clustering; Complexity theory; Dictionaries; Electromagnetism; Engineering Sciences; Excitation; Feeds; Layout; Linear antenna arrays; Linear arrays; Signal and Image processing; subarraying; Synthesis; total-variation compressive sensing (TV-CS)
• ISSN: 0018-926X; 1558-2221
• DOI: 10.1109/TAP.2019.2911375

By exploiting an innovative total-variation compressive sensing (TV-CS) formulation, a new method for the synthesis of physically contiguous clustered linear arrays is presented. The computation of the feed network excitations is recast as the maximization of the gradient sparsity of the excitation vector subject to matching a user-defined pattern. The arising TV-CS functional is then optimized by means of a deterministic alternating direction algorithm. A selected set of representative numerical results, drawn from a wide validation, is reported to illustrate the potentialities and the limitations of the proposed approach when clustering arrays of both ideal and realistic antenna elements. Comparisons with some competitive state-of-the-art subarraying techniques are performed as well.