Dokumenttyp: Artikel/Aufsatz
Titel: Determination of Intensity-Based Stochastic Models for Terrestrial Laser Scanners Utilising 3D-Point Clouds
Autor*in: Wujanz, Daniel
Burger, Mathias
Tschirschwitz, Felix 
Nietzschmann, Tassilo
Neitzel, Frank
Kersten, Thomas 
Erscheinungsdatum: 7-Jul-2018
Freie Schlagwörter: individual point quality; precision; rangefinder; stochastic modelling; terrestrial laser scanning
Zusammenfassung: 
Recent advances in stochastic modelling of reflectorless rangefinders revealed an inherent relationship among raw intensity values and the corresponding precision of observed distances. In order to derive the stochastic properties of a terrestrial laser scanner’s (TLS) rangefinder, distances have to be observed repeatedly. For this, the TLS of interest has to be operated in the so-called 1D-mode—a functionality which is offered only by a few manufacturers due to laser safety regulations. The article at hand proposes two methodologies to compute intensity-based stochastic models based on capturing geometric primitives in form of planar shapes utilising 3D-point clouds. At first the procedures are applied to a phase-based Zoller + Fröhlich IMAGER 5006h. The generated results are then evaluated by comparing the outcome to the parameters of a stochastic model which has been derived by means of measurements captured in 1D-mode. Another open research question is if intensity-based stochastic models are applicable for other rangefinder types. Therefore, one of the suggested procedures is applied to a Riegl VZ-400i impulse scanner, as well as a Leica ScanStation P40 TLS that deploys a hybrid rangefinder technology. The generated results successfully demonstrate alternative methods for the computation of intensity-based stochastic models as well as their transferability to other rangefinder technologies.
Sachgruppe (DDC): 004: Informatik
HCU-Fachgebiet / Studiengang: Photogrammetrie und Laserscanning 
Zeitschrift oder Schriftenreihe: Sensors 
Band: 18
Ausgabe: 7
Verlag: MDPI
ISSN: 1424-8220
Verlagslink (DOI): 10.3390/s18072187
URN (Zitierlink): urn:nbn:de:gbv:1373-repos-9307
Direktlink: https://repos.hcu-hamburg.de/handle/hcu/728
Sprache: Englisch
Creative-Commons-Lizenz: https://creativecommons.org/licenses/by/4.0/
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