Deep Learning Methods for Velocity Estimation based on Automotive Radar Data

Identification of object velocities in the vicinity of self-driving vehicles is of exceptional importance as it provides insights into the evolving environment. To satisfy this demand, this thesis addresses a holistic approach to environment perception, with a particular focus on velocity estimation. Specifically, pioneering artificial intelligence methods are developed to process automotive radar data.