Multi-Radar Self-Calibration Method using High-Definition Digital Maps for Autonomous Driving

Advanced Driving Assistance Systems rely on a very precise sensor-based environmental perception. The quality of the perception depends on the quality of the calibration when multiple and/or redundant sensors are used. This work presents a novel self-calibration method for radars based on high-definition digital maps and high radar-sensitive structural elements. The calibration targets are transformed from the world into the vehicle reference system according to the estimated vehicle state. Then, the calibration between the radar and the vehicle frame is split into two phases, alignment and translation estimation. The alignment is based on the trajectory described by the calibration targets when the vehicle is moving, and the translation is based on position differences when is standing. The uncertainties of the detections are treated in a scoring fashion. Three radars of two different models have been calibrated with this method achieving radar alignments below the angular accuracy and mean range errors below the radar range accuracy.