Meaning
Analytical transformation of near-field phase and amplitude measurements into distant radiation patterns introduces numerical discrepancies due to spatial sampling limits and measurement surface boundaries. Antenna integration teams quantify far field reconstruction error to evaluate how accurately planar or spherical near-field scans predict actual long-range radiation performance. Phase noise in the receiver system and mechanical misalignment of positioner stages directly increase transformation discrepancies.
Mathematical Boundary
Discrete Fourier transform algorithms process sampled near-field data to calculate plane wave spectra. Sampling intervals exceeding half a wavelength cause spatial aliasing, which propagates directly into calculated radiation patterns. Finite sampling grids truncate the spatial integration surface, distorting side lobe levels and shifting predicted null positions.
Higher order mode truncation in spherical wave expansions introduces systematic mathematical offset in calculated main beam directive gain values.
Computational Drift
Algorithm precision depends on accurate phase center determination and low phase drift during planar scan execution.
Measurement Deviation
Discrepancies between transformed fields and measured directivity patterns reveal phase calibration errors within the measurement setup. Verification procedures compare reconstructed patterns against calibrated far-field range baseline measurements. Software compensation algorithms adjust phase values based on positioner encoder feedback to reduce transformation artifacts.
The far field reconstruction error establishes the operational boundary for near-field antenna pattern extrapolation techniques.
