Multi target tracking with CPHD filter based on asynchronous sensors

In this paper, the problem of targets road tracking based on multiple asynchronous sensors is addressed. A method based on Cardinalized Probability Hypothesis Density (CPHD) filter improved with probability of target type is presented. Using the sensor classification, the probability of target type is recursively computed by Bayesian rules. This probability is used to improve the performance of the Multi Target Tracking (MTT) filter and the understanding of the observed area. The tuning of filter parameter depending of sensor is explained and the particular case of non detection due to occlusion with camera is developed. Our system has been validated with real measurements from a smart camera and a radar in real traffic conditions with real time computation.