Direct Georeferencing of Stationary LiDAR
AbstractUnlike mobile survey systems, stationary survey systems are given very little direct georeferencing attention. Direct Georeferencing is currently being used in several mobile applications, especially in terrestrial and airborne LiDAR systems. Georeferencing of stationary terrestrial LiDAR scanning data, however, is currently performed indirectly through using control points in the scanning site. The indirect georeferencing procedure is often troublesome; the availability of control stations within the scanning range is not always possible. Also, field procedure can be laborious and involve extra equipment and target setups. In addition, the conventional method allows for possible human error due to target information bookkeeping. Additionally, the accuracy of this procedure varies according to the quality of the control used. By adding a dual GPS antenna apparatus to the scanner setup, thereby supplanting the use of multiple ground control points scattered throughout the scanning site, we mitigate not only the problems associated with indirect georeferencing but also induce a more efficient set up procedure while maintaining sufficient precision. In this paper, we describe a new method for determining the 3D absolute orientation of LiDAR point cloud using GPS measurements from two antennae firmly mounted on the optical head of a stationary LiDAR system. In this paper, the general case is derived where the orientation angles are not small; this case completes the theory of stationary LiDAR direct georeferencing. Simulation and real world field experimentation of the prototype implementation suggest a precision of about 0.05 degrees (~1 milli-radian) for the three orientation angles.
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Mohamed, A.; Wilkinson, B. Direct Georeferencing of Stationary LiDAR. Remote Sens. 2009, 1, 1321-1337.
Mohamed A, Wilkinson B. Direct Georeferencing of Stationary LiDAR. Remote Sensing. 2009; 1(4):1321-1337.Chicago/Turabian Style
Mohamed, Ahmed; Wilkinson, Benjamin. 2009. "Direct Georeferencing of Stationary LiDAR." Remote Sens. 1, no. 4: 1321-1337.