Radar in the Rain: Understanding and Simulating Environmental Effects on ADAS Radar Sensors

Advanced driver assistance systems (ADAS) depend heavily on clear and precise environmental perception. It is a known issue that vision-based sensors, like cameras and LIDARs, may experience a significant performance decline in adverse weather conditions, such as heavy rain and thick fog. Radar sensors, operating in different frequency ranges, offer a partial solution by overcoming some limitations associated with vision-based environmental perception. Simulation has become an invaluable tool for validating driving functions and sensors within a virtual environment, offering the capability to replicate critical scenarios and systematically adjust weather conditions for testing. Nonetheless, the reliability of the simulation tool must be verified through validation against real-world scenarios. The effect of raindrops over the radar rays should be studied to understand the possible impact on environmental perception. This work analyses two radar sensors' measured radar cross section (RCS) under several rain conditions and proposes a model to simulate the rain effects on the radar rays. The results revealed that not only does the rain intensity play a role in the radar detection, but the asphalt condition, whether dry or wet, increases the multipath effect, reducing the accuracy of the radars. The proposed model confirms the possibility of simulating the power-loss impact by matching the limits of real measurements.