Assessment of micro-doppler based road targets recognition based on co-operative multi-sensor automotive radar applications

Radar systems have become one of the principal sensory components in automotive vehicles, due to their ability to detect and discriminate between different objects in various scenarios. In this paper the micro-Doppler signature is used to identify road targets as cyclist, person, group of people, dog walking, and dog trotting. In order to boost the performance of Automatic Target Recognition in automotive environment, each node could share its micro-Doppler based features in a co-operative manner, using novel Vehicle To Vehicle communication frameworks based on joint radar and communication systems. The classification performance is evaluated considering two scenarios, a single-sensor scenarios where the micro-Doppler signature is observed by a single user, and a multi-sensor scenarios where each user shares its feature vector.