Radar Vehicle Signatures: Comparison of Up-to-Date Automotive Radar Sensors With Different Characteristics

Abstract

The increasing angular resolution of modern automotive radar sensors enables a more detailed and more accurate perception of the environment. This has implications for the measured target detections of extended objects, such as vehicles, which cause complex backscatter signatures. Simulation-based approaches strive to enable efficient testing concepts, but require high-fidelity sensor models. To assess the impact of different sensors on the virtual replication of sensor data, it is important to examine the variations between measurements from various sensors. In this letter, radar detections of a passenger vehicle using three radars with different characteristics are presented. Similarities between the spatial distributions of the detections are revealed and differences in the number of target detections, and the accuracy of their localization within the bounding box of the vehicle are identified. Furthermore, the spatial fluctuations of point clouds between succeeding measurement cycles are investigated. The results suggest that existing data-driven modeling approaches can be applied to different sensors as well, but that particular attention must be paid to the distinct spatial spread of the detections and to the fluctuations of point clouds.