Multi-beam lidar intensity calibration by interpolating learned response curve

Abstract

Lidar intensity calibration from multi-beam lidar sensors uses calibration panels with known reflectance. The intensity response curves of each lidar beam are learned and modeled as a function of the known reflectivity, the transmission power level, and the distance. Contrary to the lidar equation, characterization of multi-beam lidar scanners commonly used for autonomous driving applications reveals that intensity does not fall-off according to the theoretically expected inverse distance-squared. Instead, a maximum intensity response is attained at a specific distance (focal distance). While the focal distance varies across beams, it is independent of the transmission power. Outside of the focal distance, distance intensity exhibits a sharp fall off. The intensity response curve of the lidar is well-approximated by a parametric form. Learned splines as functions of distance and power level determine the most likely mapping from raw data to surface reflectance along with a measure of uncertainty.