Performance analysis of a compact and low-cost mapping-grade mobile laser scanning system

Kalev Julge; Toivo Vajakas; Artu Ellmann

doi:10.1117/1.JRS.11.044003

12 December 2017 Performance analysis of a compact and low-cost mapping-grade mobile laser scanning system

Kalev Julge, Toivo Vajakas, Artu Ellmann

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 11, Issue 4, 044003 (December 2017). https://doi.org/10.1117/1.JRS.11.044003

Abstract

The performance of a low-cost, self-contained, compact, and easy to deploy mapping-grade mobile laser scanning (MLS) system, which is composed of a light detection and ranging sensor Velodyne VLP-16 and a dual antenna global navigation satellite system/inertial navigation system SBG Systems Ellipse-D, is analyzed. The field tests were carried out in car-mounted and backpack modes for surveying road engineering structures (such as roads, parking lots, underpasses, and tunnels) and coastal erosion zones, respectively. The impact of applied calculation principles on trajectory postprocessing, direct georeferencing, and the theoretical accuracy of the system is analyzed. A calibration method, based on Bound Optimization BY Quadratic Approximation, for finding the boresight angles of an MLS system is proposed. The resulting MLS point clouds are compared with high-accuracy static terrestrial laser scanning data and survey-grade MLS data from a commercially manufactured MLS system. The vertical, horizontal, and relative accuracy are assessed—the root-mean-square error (RMSE) values were determined to be 8, 15, and 3 cm, respectively. Thus, the achieved mapping-grade accuracy demonstrates that this relatively compact and inexpensive self-assembled MLS can be successfully used for surveying the geometry and deformations of terrain, buildings, road, and other engineering structures.

Citation Download Citation

Kalev Julge, Toivo Vajakas, and Artu Ellmann "Performance analysis of a compact and low-cost mapping-grade mobile laser scanning system," Journal of Applied Remote Sensing 11(4), 044003 (12 December 2017). https://doi.org/10.1117/1.JRS.11.044003

Received: 19 June 2017; Accepted: 14 November 2017; Published: 12 December 2017

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