Abstract
An effective near-field - far-field (NF - FF) transformation with spherical scanning for quasi-planar antennas from irregularly spaced data is developed in this paper. Two efficient approaches for evaluating the regularly spaced spherical samples from the nonuniformly distributed ones are proposed and numerically compared. Both the approaches rely on a nonredundant sampling representation of the voltage measured by the probe, based on an oblate ellipsoidal modelling of the antenna under test. The former employs the singular value decomposition method to reconstruct the NF data at the points fixed by the nonredundant sampling representation and can be applied when the irregularly acquired samples lie on nonuniform parallels. The latter is based on an iterative technique and can be used also when such a hypothesis does not hold, but requires the existence of a biunique correspondence between the uniform and nonuniform samples, associ- ating at each uniform sampling point the nearest irregular one. Once the regularly spaced spherical samples have been recovered, the NF data needed by a probe compensated NF - FF transformation with spherical scanning are efficiently evaluated by using an optimal sampling interpolation algorithm. It is so possible to accurately compensate known posi- tioning errors in the NF - FF transformation with spherical scanning for quasi-planar antennas. Some numerical tests assessing the accuracy and the robustness of the proposed approaches are reported.
Highlights
Near-field - far-field (NF - FF) transformation techniques [1,2,3,4,5] have been widely investigated in the last four decades and used for applications ranging from cellular phone antennas to large phased arrays and complex multi-beam communication satellite antennas
The application of the nonredundant sampling representations of the EM field [18] has allowed a significant reduction of the number of needed NF data when considering antennas having one or two predominant dimensions [13]. These results have been achieved by assuming the antenna under test (AUT) as enclosed in a prolate or oblate ellipsoid and by developing an optimal sampling interpolation (OSI) formula, which allows the reconstruction of the data required by the abovementioned NF - FF transformation
The aim of this paper is to develop and compare numerically analogous algorithms to compensate the probe positioning errors in the NF - FF transformation with spherical scanning for quasi-planar antennas, which will be assumed as enclosed in an oblate ellipsoid instead of a prolate one
Summary
Needed NF data when considering antennas having one or two predominant dimensions [13]. With reference to a plane-polar and cylindrical geometry, this limitation has been overcome in [24] and [25], respecttively, by developing an approach based on the use of the singular value decomposition (SVD) method [26] This latter approach allows one to take advantage of data redundancy for increasing the algorithm stability, but can be conveniently applied when the two-dimensional problem of the uniform samples recovery can be tackled as two independent one-dimensional ones, otherwise the dimension of the involved matrix would become very large, requiring a huge computational effort.
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