Intensity-based stochastic model of terrestrial laser scanners: Methodological workflow, empirical derivation and practical benefit

Abstract

After more than twenty years of commercial use, laser scanners have reached technical maturity and consequently became a standard tool for 3D-data acquisition across various fields of application. Yet, meaningful stochastic information regarding the achieved metric quality of recorded points remains an open research question. Recent research demonstrated that raw intensity values can be deployed to derive stochastic models for reflectorless rangefinders. Yet, all existing studies focused on single instances of particular laser scanners while the derivation of the stochastic models required significant efforts.

Motivated by the aforementioned shortcomings, the focus of this study is set on the comparison of stochastic models for a series of eight identical phase-based scanners that differ in age, working hours and date of last calibration. In order to achieve this, a standardised methodological workflow is suggested to derive the unknown parameters of the individual stochastic models. Based on the generated outcome, a comparison is conducted which clarifies if a universally applicable stochastic model (type calibration) can be used for a particular scanner model or if individual parameter sets are still required for every scanner (instance calibration) to validate the practical benefit and usability of those models. The generated results successfully demonstrate that the computed stochastic model is transferable to all individual scanners of the series.