Airborne laser scanning (ALS) of urban regions is commonly used as a basis for subsequent city modeling. In this process, data acquisition relies highly on the quality of GPS/INS 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 at using an existing georeferenced city model to correct errors of the assumed sensor position, which is measured under non-differential GPS and/or INS drift conditions. Our approach accounts for guidance of helicopters or UAVs over known urban terrain even at night and during frequent loss of GPS signals. We discuss several possible sources of errors in airborne laser scanner systems and their influence on the measured data. A workflow of real-time capable methods for the segmentation of planar surfaces within ALS data is described. Matching planar objects, identified in both the on-line 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 subsequent city modeling. In this process, data acquisition relies highly on the quality of GPS/INS 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 at using an existing georeferenced city model to correct errors of the assumed sensor posi...
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