Image-Based Pedestrian Classification for 79 GHz Automotive Radar

Radar sensors have become an integral part of advanced driver assistance systems. Merely detecting targets will not, however, advance their contribution. Rather, an object classification capability is required to distinguish vulnerable road users from other objects, such as vehicles. In this paper, we present a novel pedestrian classification procedure, which uses image features from the range-Doppler-Matrix created by a 79 GHz chirp sequence radar. Experiments show single measurement success rates of 88% for a bandwidth of 1.6 GHz. Moreover, the robustness of the classification process is consolidated with a tracking algorithm. Implemented in vehicles, this can be a major contribution to protect vulnerable road users.