This communication provides the experimental validation of an effective probe-compensated near-field to far-field (NF-FF) transformation with a nonconventional plane-rectangular scan suitable for flat antennas under test (AUTs). It is based on the nonredundant sampling representations of the electromagnetic fields, on the use of optimal sampling interpolation expansions, and assumes a flat AUT as enclosed in a dish having diameter equal to its maximum dimension. This source modeling results to be very effective from the NF data reduction viewpoint, since, by fitting very well the geometry of such a kind of AUT, it is able to reduce as much as possible the residual volumetric redundancy related to the use of the other modelings suitable for quasi-planar AUTs (an oblate spheroid or a double bowl). Experimental results, assessing the practical feasibility of the proposed NF-FF transformation technique, are shown.

A Near-Field to Far-Field Transformation with Noncanonical Plane-Rectangular Scan Using an Effective AUT Modeling

Bevilacqua F.;D'Agostino F.;Ferrara F.;Gennarelli C.;Guerriero R.;Migliozzi M.
2021-01-01

Abstract

This communication provides the experimental validation of an effective probe-compensated near-field to far-field (NF-FF) transformation with a nonconventional plane-rectangular scan suitable for flat antennas under test (AUTs). It is based on the nonredundant sampling representations of the electromagnetic fields, on the use of optimal sampling interpolation expansions, and assumes a flat AUT as enclosed in a dish having diameter equal to its maximum dimension. This source modeling results to be very effective from the NF data reduction viewpoint, since, by fitting very well the geometry of such a kind of AUT, it is able to reduce as much as possible the residual volumetric redundancy related to the use of the other modelings suitable for quasi-planar AUTs (an oblate spheroid or a double bowl). Experimental results, assessing the practical feasibility of the proposed NF-FF transformation technique, are shown.
2021
978-1-7362351-1-9
978-1-7362351-3-3
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4777422
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