Correlating Intrinsic Parameters and Sharpness for Condition Monitoring of Automotive Imaging Sensors

With the recent transformation of the automotive industry towards electrified and partially automated driving, the responsibility for reliable environmental perception moves from the driver to the vehicles advanced driving assistance systems (ADAS). As a consequence, the respective sensor systems are becoming more and more safety critical, as well as a major cost driver in modern vehicles. A large portion of automotive sensors consist of imaging devices like mono and stereo cameras for object detection, as well as currently emerging, non-scanning solid-state LiDAR (Light Detection And Ranging) sensors. Within this work, we investigate key parameters to monitor the thermo-mechanical state of the sensor optics and its impact on imaging quality during vehicle operation. Therefore, the intrinsic calibration parameters and modulated transfer function of a commercial, indirect time-of-flight camera were measured under varying operating temperatures in order to uncover major correlations. By doing so, it could be shown that thermally induced deformations within the optical path and the corresponding loss of sharpness can - to a certain extend - be predicted by accurate camera calibration. Hence, this work aims to motivate precise in-field camera re-calibration to continuously monitor the sensors optical system condition.