Classification and Tracking of Moving Objects from 77 GHz Automotive Radar Sensors

Automotive radar sensors play critical roles in self-driving that would revolutionize transport and shape the society. How to process automotive data and sense the environment has become a study of concern. This paper presents a study of objective classification and tracking based on a set of measured data from 4 high performance 77 GHz radar sensors mounted on a vehicle moving in a complex environment. The radar data is processed dynamically in frames with integrated three processing techniques i) the clustering processing based on DBSCAN clustering method, ii) the tracking processing based on Kalman Filter, and iii) the classification processing by studying the features of clusters of different categories of road users.