%A Marco SALUCCI
%A Nicola ANSELMI
%A Andrea MASSA
%X A novel methodology for robust near-field (NF) antenna characterization, based on probabilistic
  sparsity, is proposed. This method leverages the measurements-by-design (MebD) paradigm and
  incorporates prior knowledge of the antenna under test (AUT) to construct an overcomplete
  representation basis. Subsequently, a Bayesian strategy is employed to solve the reformulated problem.
  Representative numerical results are provided to demonstrate the efficacy of our approach in reducing
  the burden/cost of the acquisition process and mitigating potential truncation errors.
%D 2024
%K Antenna measurements, antenna qualification, compressive sensing, near-field pattern estimation, near-field to far-field transformation, sparsity retrieval, truncation error.
%L elediasc12877
%I ELEDIA Research Center - University of Trento
%T Advancements in Near-Field Antenna Characterization: A Compressive Sensing Perspective