TY  - RPRT
N2  - 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.
M1  - technical_report
Y1  - 2024///
UR  - http://www.eledia.org/students-reports/877/
TI  - Advancements in Near-Field Antenna Characterization: A Compressive Sensing Perspective
KW  - Antenna measurements
KW  -  antenna qualification
KW  -  compressive sensing
KW  -  near-field pattern estimation
KW  -  near-field to far-field transformation
KW  -  sparsity retrieval
KW  -  truncation error.
PB  - ELEDIA Research Center - University of Trento
AV  - public
A1  - SALUCCI, Marco
A1  - ANSELMI, Nicola
A1  - MASSA, Andrea
ID  - elediasc12877
ER  -