IMMPDA vehicle tracking system using asynchronous sensor fusion of radar and vision

This paper focuses on recognition and tracking of maneuvering vehicles in dense traffic situations. We present an asynchronous multi obstacle multi sensor tracking method that fuses information from radar and monocular vision. A low level fusion method is integrated into the framework of an IMMPDA Kalman filter. Real world experiments demonstrate that the system combines the complementary strengths of the employed sensors.