@techreport{elediasc12793,
          author = {Marco SALUCCI and Angelo GELMINI and Giacomo OLIVERI and Andrea MASSA},
            year = {2019},
           title = {Diagnosis of Planar Phased Arrays Through a Probabilistic Compressive Sensing Approach},
            type = {Technical Report},
       publisher = {ELEDIA Research Center - University of Trento},
             url = {http://www.eledia.org/students-reports/793/},
        abstract = {This  work  deals  with  the  detection  of  faulty elements  in  planar  phased  antenna arrays  starting  from  far?field  pattern  measurements. Owing  to  the  intrinsically sparse  nature  of  the  problem  unknowns  at  hand,  the diagnosis  problem  is formulated as a probabilistic Compressive Sensing (CS) one and it is effectively and efficiently solved through a customized Bayesian CS (BCS) solution approach. Some representative synthetic benchmarks are shown in order to verify the potentialities as well as the current limitations of the proposed BCS?based diagnosis tool, as well as to assess its flexibility in dealing with arbitrary excitation taperings of the AUT.},
        keywords = {Antenna arrays, array failure, Bayesian compressive sensing (BCS), compressive sensing, fault diagnosis, planar arrays}
}