A Bayesian Compressive Sensing Method for Robust Diagnosis of Planar Arrays from Far‐Field Measurements

SALUCCI, Marco and GELMINI, Angelo and OLIVERI, Giacomo and MASSA, Andrea (2019) A Bayesian Compressive Sensing Method for Robust Diagnosis of Planar Arrays from Far‐Field Measurements. Technical Report. ELEDIA Research Center - University of Trento.

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Abstract

In this work, the diagnosis of planar phased antenna arrays from far‐field measurements is addressed. The inverse problem at hand is formulated as a sparse retrieval one devoted at reconstructing the faulty radiators within the antenna under test. Towards this end, a Bayesian compressive sensing (BCS)‐based method is developed to deal with the planar array diagnosis without requiring that the involved measurement operator a‐priori satisfies the restricted isometry property (RIP). Furthermore, the proposed diagnosis tool is able to take into account the presence of real radiators, as well as to consider mutual coupling effects arising in realistic operative conditions. Some representative numerical examples are presented in order to verify the effectiveness of the proposed diagnosis tool.

Item Type: Monograph (Technical Report)
Uncontrolled Keywords: Antenna arrays, array failure, Bayesian compressive sensing (BCS), compressive sensing, fault diagnosis, planar arrays.
Subjects: A Areas > A WC Next Generation Wireless Communications
M Methodologies > M CS Compressive Sensing
URI: http://www.eledia.org/students-reports/id/eprint/794

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