Abstract
Abstract. Terrestrial laser scanning (TLS) instruments find routine use for a range of precision engineering measurement applications. Depending on the accuracy requirements for a specific project, the instrument may require self-calibration to determine systematic error model terms. One of the goals of first-order network design for self-calibration is to acquire observations throughout the full instrumental field-of-view. Experience calibrating TLS instruments has demonstrated that while this goal can be achieved for horizontal deflection angle observations, it is seldom realized for the vertical angle observations. This paper presents results from a preliminary investigation into the impact of the distribution of vertical angle observations on the estimation of two critical systematic error parameters in TLS instruments: the collimation axis error and the trunnion axis error. First, a model to characterize the empirical observation distributions is developed. The model is a function of a single shape parameter that quantifies observation dispersion. Then, a means to estimate the impact of the distribution on the parameter estimation is developed. Results from six real datasets show the distribution model characterizes the overall general trend of the observations. Simulated results show the relative independence of the collimation axis error and the strong dependence of the trunnion axis error on the shape parameter.
Highlights
1.1 Terrestrial Laser Scanner CalibrationSensor modelling and calibration are recognized as important quality assurance processes for terrestrial laser scanning (TLS) instruments used for precise engineering measurement projects
Systematic errors inherent to TLS instruments must be identified and the model parameters estimated so that acquired point clouds can be corrected in order to maximize accuracy
There is a wide range of values for the shape parameter α0: from 50° to more than 80°
Summary
Sensor modelling and calibration are recognized as important quality assurance processes for terrestrial laser scanning (TLS) instruments used for precise engineering measurement projects. Systematic errors inherent to TLS instruments must be identified and the model parameters estimated so that acquired point clouds can be corrected in order to maximize accuracy. A geometrically strong network is generally regarded as essential to the accurate estimation of systematic error parameters. Lichti (2007) reports that a large elevation angle range is needed for the estimation of certain error terms. Lichti (2010) used simulation to investigate the impact of the range of elevation angle measurements on the precision of and the correlation between certain model variables. This work focuses on modelling and quantifying the impact of the distribution of angular observations within a TLS self-calibration network
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