Surface Side Influences on the Reflectorless Distance Measurement
The application of terrestrial laser scanning (TLS) in engineering geodesy requires adequate stochastic and functional error model of measured observations. These are fundamental prerequisites for data processing and for the evaluation of results in general as well as for TLS self-calibration in particular. Therefore, systematic error influences acting on the measurement need to be investigated and modelled correspondingly.
The error model needs to include influences that come from reflectorless (RL) distance measurement. As the transmitted laser (the measuring signal) is directly reflected from the measured object each single measurement is influenced slightly different by the object properties and the measuring configuration. Some examples are the changing orientation of the object relative to the measurement beam which leads to different incidence angles, the distance variation to the object and the different roughness, refractive index, absorption coefficient of the object etc. Each object’s property or a combination of these, influence the reflection and thus cause systematic and stochastic distance deviations.
A large amount of investigations pointed out that the results of RL-measurements are influenced by combinations of the object side influences. Thus, establishing a sought error model is a complex and hard task.
This presentation is primarily devoted to the influence of the incidence angle on RL-measurements. Secondary its combination with varying distance and roughness level of the measured object from one material is investigated. The distance measurement deviations due to the abovementioned factors were quantified using a methodology originally developed for scanned total stations, optimized over epochs and nowadays suitable for each TLS. Its uniqueness is that individual measured distances in scanning mode are investigated instead of making any assumptions on the geometric and radiometric properties of the object. Presented results describe properties of the examined influences and contribute to the error model of RL-measured distances.