  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.
