This report presents the results of investigations to determine accurate positions of
aircrafts in airborne surveys (airborne gravity and airborne lidar) using precise point
positioning, and also introduces a new so called “stepwise geometric misalignment
determination” method to retrieve the airborne lidar system misalignment angle by
automating the matching of lidar data with ground truth.
Kinematic GPS positioning has been widely used, but the available commercial
software systems are normally only suitable for the short or medium range kinematic
baseline. However, in polar areas, airborne surveys have baselines ranging from a few
hundred kilometers to even more than one thousand kilometers due to logistic
limitations. It is a challenge to the traditional kinematic GPS software based on
double differenced models, such as GPSurvey or GrafNav. Since Zumberge
demonstrated the perfect performance of point positioning for kinematic applications,
the precise point positioning attracted a lot of attention and opened a new alternative
door to kinematic positioning.
In this report different tests have been done to evaluate the ability and accuracy of the
software TriP in the kinematic and static case by using internal consistency (residuals,
RMS, repeatability etc.), known coordinates, ground truth and double-differenced
solutions. The kinematic GPS positioning accuracy using four different software
systems has been investigated and tested by comparing the degree of agreement
between ground truth and the height of airborne lidar footprints derived from
combining flight trajectory, orientation and lidar range. The conclusion is that the
TriP software is robust and reliable, and that TriP runs much faster (10 times) than
GPSurvey 2.30. A static positioning accuracy of mm to cm level could be achievable
depending on the observation session length, and kinematic positioning accuracy can
reach cm to dm level.
Furthermore, a new method for airborne lidar system misalignment calibration was
described in detail. The proposed method was a so called ‘stepwise geometric
misalignment determination’ based on the relationship between the point clouds on
regular objects (e.g. flat top buildings) and the ground truth of the objects used for
calibration. In order to extract the footprints on the objects, filtering was implemented
before the calibration. Three example tests have been made and verified that the
proposed method is feasible and effective.