Mobile scanning, i.e., the practice of mounting laser scanners on moving platforms is an efficient way to acquire accurate and dense 3D point clouds of outdoor environments for urban and regional planning and architecture. The mobile scenario puts high requirements on the accuracy of the calibration of the measurement system, as small calibration inaccuracies lead to large errors in the resulting point cloud. We propose a novel algorithm for the calibration of a mobile scanning system that estimates the calibration parameters for
sensor components simultaneously without relying on additional hardware. We evaluate the calibration algorithm on several real world data sets where ground truth is available via an accurate geodetic model.