@techreport{elediasc12795,
            type = {Technical Report},
          author = {Marco SALUCCI and Angelo GELMINI and Giacomo OLIVERI and Andrea MASSA},
           title = {Robust Diagnosis of Microstrip Planar Phased Arrays Through a Compressive Sensing Approach},
            year = {2019},
       publisher = {ELEDIA Research Center - University of Trento},
        keywords = {Antenna arrays, array failure, Bayesian compressive sensing (BCS), compressive sensing, fault diagnosis, planar arrays},
             url = {http://www.eledia.org/students-reports/795/},
        abstract = {This work deals with the detection of faulty radiators in real microstrip patches planar phased arrays. Towards this goal, the diagnosis problem at hand is formulated within a probabilistic compressive sensing (CS) framework in order to avoid the fulfillment of the restricted isometry property (RIP) by the involved measurement operator. A customized Bayesian CS solution approach is then developed to yield robust and reliable guesses of the antenna under test (AUT) status by also taking into account all mutual coupling effects arising in realistic operative conditions. Some numerical benchmarks are shown to assess the effectiveness of the proposed diagnosis tool when considering a variation of the antenna size and failure rate, as well as a change of the amount of noise on processed far-field data.}
}