Optical path design facing θ/θ reflectance measurement of test targets for autonomous vehicles

As a pair of "wise eyes" for autonomous vehicles to perceive the external environment, Lidar (Light detecting and Ranging) plays a crucial role in detecting target characteristics in driving scenarios. To ensure the accuracy and reliability of Lidar, precise measurement of target reflectance under θ/θ reflection conditions is an indispensable step. Determining the reflectance value of targets under θ/θ reflection conditions is a critical part of completing Lidar calibration and traceability. When designing the θ/θ optical path, a significant challenge lies in achieving almost perfect overlap between the lighting and detecting paths while ensuring system compactness and measurement accuracy. Fiber optic spectrometers, known for their fast and accurate measurement capabilities, can be directly applied to measure target reflectance. Therefore, combining a compact θ/θ reflection optical path with a fiber optic spectrometer is key to achieving small-angle reflectance measurements for Lidar, marking an important step towards improving the calibration and traceability chain. For Lidar under θ/θ reflection conditions, various "N+1" lighting/detecting combined optical paths based on fiber bundles have been designed. Simulation analysis of these designs has been conducted using ray-tracing methods, comparing the uniformity and optical flux efficiency of the tested samples. The results indicate that when N=6, the uniformity and incident flux efficiency are optimal. Based on the simulation results, a "6+1" lighting/detecting fiber optic spectrometer has been developed, and actual measurements have been performed on a standard diffuser. The measurement data shows that the angular accuracy under 0/0 and 45/45 conditions is better than 0.1°, and the optimal relative error of the reflection measurement results in the 905nm laser wavelength was less than 0.5%. This meets the requirements for on-site measurements and is significant for further improving the Lidar measurement traceability chain.