New Strategies for Integrating Photogrammetric and Gnss Data

GNSS-controlled photogrammetry is a mature technology that has found near universal acceptance in the aerial mapping community. The current strategy for integrating photogrammetric and GNSS data is to first process the GNSS data using a stand-alone kinematic Kalman filter processor, and then to use the resulting positions as parameter observations in a photogrammetric bundle adjustment. The utility of this implementation has been well-proven; however, there has been little research into other integration strategies. In this paper, investigations are made into some alternative integration approaches. Focus is given to two techniques: first, an approach with improved information-sharing between the GNSS and photogrammetric processors, and second, a combined least-squares adjustment of the raw GNSS and photogrammetric measurements. After providing background on the existing integration strategies, the new approaches are introduced and detailed. Tests are made using a standard aerial block, results from which appear to indicate that the new techniques do not improve mapping accuracy over the conventional approach. The new techniques, however, may improve GNSS positioning accuracy or enable some more unique network configurations.