von Herrn Niko Fauter
Kurzfassung:
Tracking of extended objects, such as other vehicles, is an essential yet challenging
part of autonomous driving and advanced driver assistance systems. These
systems rely on the accurate tracking of vehicles as a prerequisite for accurate planning
and decision making.
The tracking is based on different sensors that deliver data at different levels of preprocessing.
This work proposes a Hybrid Multi-Sensor Filter that includes radar measurements into an existing tracking framework.
To solve the data association problem a sum-product algorithm for scalable extended object tracking is used.
The results show that including radar data increases robustness and enhances estimation.
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