A Radar Measurement Model for Extended Object Tracking in Dynamic Scenarios.

The radar sensor is an important component in autonomous driving applications. Compared with other sensor types like LiDAR or camera, the radar sensor comes with best weather robustness and ease of integration. Its exclusive capability to measure electromagnetic reflectivity and Doppler-derived radial speeds plays a major role in environment perception applications. However, the processing chain of the radar is more complex and often results in unintuitive measurement effects. In this paper, we explain the technical background of high-resolution radar detections. We give a probabilistic architecture modeling Doppler and Micro-Doppler measurements and their influence on the Monopulse-based azimuth angle, the peak detection and the resulting measurement data. Examples accompany the description of the modeling steps.