The general demand for the prevention of collateral damages in military operations requires methods of robust automatic
identification of target objects like vehicles especially during target approach. This requires the development of
sophisticated techniques for automatic and semi-automatic interpretation of sensor data. In particular the automatic pre-analysis
of reconnaissance data is important for the human observer as well as for autonomous systems. In the phase of
target approach fully automatic methods are needed for the recognition of predefined objects. For this purpose
appropriate sensors are used like imaging IR sensors suitable for day/night operation and laser radar supplying 3D
information of the scenario. Classical methods for target recognition based on comparison with synthetic IR object
models imply certain shortcomings, e.g. unknown weather conditions and the engine status of vehicles.
We propose a concept of generating efficient 2D templates for IR target signatures based on the evaluation of a precise
3D model of the target generated from real multisensor data. This model is created from near-term laser range and IR
data gathered by reconnaissance in advance to gain realistic and up-to-date target signatures. It consists of the visible part
of the object surface textured with measured infrared values. This enables recognition from slightly differing viewing
angles. Our test bed is realized by a helicopter equipped with a multisensor suite (laser radar, imaging IR, GPS, and
IMU). Results are demonstrated by the analysis of a complex scenario with different vehicles.
The increasing demand for the protection of persons and facilities requires the application of sophisticated technologies
for surveillance and object tracking. For this purpose appropriate sensors are used like imaging IR sensors suitable for
day/night operation and laser radar supplying 3D information of the scenario. In this context there is a requirement of
automatic and semi-automatic methods supporting the human observer in his decision-making process. A prevalent task
is automatic tracking of striking objects like vehicles or individual persons in an image sequence during a time slice.
Classical methods are based on template matching implying certain shortcomings concerning homogeneous background
or passing objects occluding the target object. The authors propose a new concept for generating templates for IR target
signatures based on the interpretation of laser range data in order to optimize the tracking process. The testbed is realized
by a helicopter equipped with a multisensor suite (laser radar, imaging IR, GPS, IMU). Results are demonstrated by the
analysis of an exemplary data set. A vehicle situated in a complex scenario is acquired by a forward moving sensor
platform and is tracked robustly by the proposed method.