A Bayesian Compressive Sensing Approach to Robust Near-Field Antenna Characterization
نویسندگان
چکیده
A novel probabilistic sparsity-promoting method for robust near-field (NF) antenna characterization is proposed. It leverages on the measurements-by-design (MebD) paradigm, and it exploits some a priori information under test (AUT) to generate an overcomplete representation basis. Accordingly, problem at hand reformulated in compressive sensing (CS) framework as retrieval of maximally sparse distribution (with respect basis) from reduced set measured data, then, solved by means Bayesian strategy. Representative numerical results are presented to, also comparatively, assess effectiveness proposed approach reducing “burden/cost” acquisition process mitigate (possible) truncation errors when dealing with space-constrained probing systems.
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ژورنال
عنوان ژورنال: IEEE Transactions on Antennas and Propagation
سال: 2022
ISSN: ['1558-2221', '0018-926X']
DOI: https://doi.org/10.1109/tap.2022.3177528