Error Characterization of Laser Scanner-Based Metrology for Large Reflector Antennas: Effects of Tilt and Measurement Noise

This repository contains two datasets used in the research submitted to IEEE Transactions on Instrumentation and Measurement on the error characterization of terrestrial laser scanner (LS) metrology for large reflector antennas. The first dataset comprises controlled laboratory measurements acquired using a FARO Focus LS mounted on a pan-and-tilt system. The LS was operated at nine tilt angles ranging from 0\u00b0 to 80\u00b0 in 10\u00b0 increments. For each tilt angle, nine FARO spherical targets were scanned, and 36 inter-sphere baselines were computed. Variations in these baselines across tilt angles were used to assess the effect of LS tilt on measurement accuracy. Each dataset contains the 3D coordinates (X, Y, Z) of the sphere centers relative to the LS position. In total, nine datasets are provided, corresponding to the nine LS tilt angles.  The second dataset consists of ten CSV files, each representing point-cloud measurements of the 30-m Cassegrain antenna\u2019s main reflector (MR) at ten different elevation angles. Each file contains approximately 20,000 subsampled 3D points (X, Y, Z) referenced to the LS coordinate frame. These data were originally used in https:\/\/dx.doi.org\/10.1142\/S2251171719500107 to estimate the elevation-dependent surface accuracy of the MR. In the present work, the dataset is reused to perform Monte Carlo error propagation for computing uncertainty (error bars) in RMS surface residuals.Together, these datasets enable the full reproducibility of the results presented in the manuscript, including tilt-induced geometric distortion analysis, two-face calibration assessment, Monte Carlo-based uncertainty propagation, and characterization of elevation-dependent reflector surface error. They also serve as an example dataset for future work in LS uncertainty modelling, reflector metrology, and large-aperture antenna assessment.