@techreport{elediasc12800,
       publisher = {ELEDIA Research Center - University of Trento},
          author = {Nicola Anselmi and Giorgio Gottardi and Giacomo Oliveri and Andrea Massa},
           title = {A Total?Variation Compressive Sensing Approach for the Design of Linear Clustered Arrays},
            type = {Technical Report},
             url = {http://www.eledia.org/students-reports/800/},
        keywords = {Clustered arrays, linear arrays, subarraying, total-variation compressive sensing (TV-CS)},
        abstract = {In  this  work,  an  innovative  methodology  for  the  design  of  physically?contiguous clustered  linear  arrays  is  proposed.  The  developed  approach  is  based  on  a sparseness?promoting  method  based  on  a  total?variation  compressive  sensing  (TV?CS)  solver.  Thanks  to  the  adopted  formulation,  the  design  of  the  array  feeding 
network  is  achieved  by  maximizing  the  sparsity  of  the  gradient  of  the  excitations subject  to  the  matching  of  user?defined  far?field  pattern  features.  A  preliminary numerical example is provided to verify  the effectiveness of  the proposed method when  dealing  with  the  design  of  a  clustered  linear  array  yielding  a  Taylor  pattern with predefined side?lobe level.}
}