  A complete overview of the surrounding vehicle environment is important for
driver assistance systems and highly autonomous driving. Fusing results of
multiple sensor types like camera, radar and lidar is crucial for increasing
the robustness. The detection and classification of objects like cars, bicycles
or pedestrians has been analyzed in the past for many sensor types. Beyond
that, it is also helpful to refine these classes and distinguish for example
between different pedestrian types or activities. This task is usually
performed on camera data, though recent developments are based on radar
spectrograms. However, for most automotive radar systems, it is only possible
to obtain radar targets instead of the original spectrograms. This work
demonstrates that it is possible to estimate the body height of walking
pedestrians using 2D radar targets. Furthermore, different pedestrian motion
types are classified.
