Two different approaches for compensating the probe positioning errors in a near-field-far-field transformation with cylindrical scanning using a nonredundant number of measurements are presented and experimentally validated in this paper. In order to evaluate the uniformly distributed samples from the irregularly spaced ones, the former makes use of the singular value decomposition method, whereas the latter employs an iterative technique. In both the cases, the near-field data needed by a standard nearfield-far-field transformation are efficiently evaluated via an optimal sampling interpolation algorithm.
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