Probabilistic short range radar data fusion
Eric Richter, Frederik Preckwinkel, Gerd Wanielik · 2012
This paper demonstrates a system which uses two short range radar sensors and on-board kinematic sensors in order to track vehicles driving behind the ego vehicle. For that, integrated probabilistic data association and the unscented Kalman filtering framework is utilized. The functionality of the proposed system is shown using real data and its performance is critically discussed.