The experimental validation of an efficient iterative technique for compensating known position errors in a spherical near to far-field transformation (NTFFT) for elongated antennas using a minimum number of near-field (NF) measurements has been provided. This transformation exploits a non-redundant sampling representation of the voltage detected by the probe obtained by modeling a long antenna with a prolate ellipsoid. The uniform samples, those at the points set by the representation, are accurately reconstructed from the acquired not regularly distributed ones (non-uniform samples) by using an iterative scheme, which requires a one to one relationship between each uniform sampling point and the corresponding non-uniform one. Then a 2-D optimal sampling formula is adopted to evaluate the input data needed to perform the traditional spherical NTFFT from the so retrieved non-redundant uniform samples. It must be stressed that the availability of an effective and robust procedure, allowing an accurate retrieval of the NF data to be used in the NTFFT from the positioning errors affected ones, is of crucial importance since, due to a not accurate control of the positioners and/or to their limited resolution, it could not be possible to get the NF measurements at the points prescribed by the non-redundant sampling representation, even if the positions of the ac¬tual acquisition points can be precisely revealed via laser interferometric techniques. Laboratory proofs, performed by using the roll-over-azimuth spherical NF scanning system available at the Antenna Characterization Lab of the University of Salerno, have demonstrated the validity of the presented technique from a practical viewpoint by comparing the very good NF and FF reconstructions achieved when employing it in presence of large and pessimistic positioning errors with those worsened obtained when this procedure is not applied.
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Reference: Cicchetti R, et al. Correction of Known Position Errors in a Spherical Near to Far-Field Transformation for Long Antennas. The Open Electrical & Electronic Engineering Journal, 2017, Vol 11, DOI: 10.2174/1874129001711010141
The Open Electrical & Electronic Engineering Journal