Airborne laser scanning (ALS) of urban regions is commonly used as a basis for city modeling. In this process, data acquisition relies heavily on the quality of positioning techniques. Typically, the use of differential GPS and high-precision GPS/INS postprocessing methods are essential to achieve the required accuracy that leads to a consistent database. Contrary to that approach, we aim to use an existing georeferenced city model to correct errors of the assumed sensor position, which is measured under standard GPS and/or INS drift conditions. Our approach accounts for navigation of UAVs or helicopters over known urban terrain, even at night and even in case of a sudden loss of GPS signals. We discuss several possible sources of error in airborne laser scanner systems and their influence on the measured data. A workflow consisting of real-time capable methods for the segmentation of planar surfaces within ALS data is described. Matching planar objects, identified in both the online segmentation results and the existing city model, are used to correct absolute errors of the sensor position.
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Airborne laser scanning (ALS) of urban regions is commonly used as a basis for city modeling. In this process, data acquisition relies heavily on the quality of positioning techniques. Typically, the use of differential GPS and high-precision GPS/INS postprocessing methods are essential to achieve the required accuracy that leads to a consistent database. Contrary to that approach, we aim to use an existing georeferenced city model to correct errors of the assumed sensor position, which is measu...
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