  Currently, digital maps are indispensable for automated driving. However, due
to the low precision and reliability of GNSS particularly in urban areas,
fusing trajectories of independent recording sessions and different regions is
a challenging task. To bypass the flaws from direct incorporation of GNSS
measurements for geo-referencing, the usage of aerial imagery seems promising.
Furthermore, more accurate geo-referencing improves the global map accuracy and
allows to estimate the sensor calibration error. In this paper, we present a
novel geo-referencing approach to align trajectories to aerial imagery using
poles and road markings. To match extracted features from sensor observations
to aerial imagery landmarks robustly, a RANSAC-based matching approach is
applied in a sliding window. For that, we assume that the trajectories are
roughly referenced to the imagery which can be achieved by rough GNSS
measurements from a low-cost GNSS receiver. Finally, we align the initial
trajectories precisely to the aerial imagery by minimizing a geometric cost
function comprising all determined matches. Evaluations performed on data
recorded in Karlsruhe, Germany show that our algorithm yields trajectories
which are accurately referenced to the used aerial imagery.
