Advances in Automated Error Assessment of Spherical Near-Field Antenna Measurements
Authors: Patrick Pelland, Greg Hindman, William Heruska, Allen Newell
Publication: EuCAP 2013
Copyright Owner: IEEE
Over the years, spherical near-field (SNF) antenna measurements have become increasingly popular for characterizing a wide variety of antenna types. The SNF configuration allows one to measure data over a sphere surrounding the antenna, which provides it a unique advantage over planar and cylindrical near-field systems where measurement truncation is inherent. Like all antenna measurement configurations, SNF systems are susceptible to a number of measurement errors that, if not properly understood, can corrupt the antenna’s far-field parameters of interest (directivity, beamwidth, beam pointing, etc.). The NIST 18-term error assessment originally developed for planar near-field measurements  has been adapted for SNF systems  and provides an accurate measure of the uncertainty in a particular SNF measurement. Once particular measurement errors are known, steps can be taken to reduce their impact on far-field radiation patterns. When manually assessing all 18 terms of the NIST uncertainty budget this procedure becomes tedious and time consuming.
This paper will describe an acquisition algorithm that allows one to analyze all 18 error terms or a subset of those in automated fashion with minimal user intervention. Building upon previous research toward developing an automated SNF error assessment algorithm [3, 4], this new procedure will automatically generate tabulated and plotted uncertainty data for directivity, beamwidth and beam pointing of a particular farfield radiation pattern. Once measurement uncertainties are known, various post-processing techniques can be applied to improve far-field radiation patterns. Results will be shown for three antennas measured on large phi-over-theta SNF scanners.
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Copyright 2013 IEEE. Reprinted from The Fifth European Conference on Antennas and Propagation (EuCAP 2013) 08-12 April 2013.
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