In order to retrieve a highly accurate view of their environment, autonomous cars are often equipped with LiDAR sensors. These sensors deliver a three dimensional point cloud in their own co-ordinate frame, where the origin is the sensor itself. However, the common co-ordinate system required by HAD (Highly Autonomous Driving) software systems has its origin at the center of the vehicle’s rear axle. Thus, a transformation of the acquired point clouds to car co-ordinates is necessary, and thereby the determination of the exact mounting position of the LiDAR system in car coordinates is required. Unfortunately, directly measuring this position is a time-consuming and error-prone task. Therefore, different approaches have been suggested for its estimation which mostly require an exhaustive test-setup and are again time-consuming to prepare. When preparing a high number of LiDAR mounted test vehicles for data acquisition, most approaches fall short due to time or money constraints. In this paper we propose an approach for mounting position estimation which features an easy execution and setup, thus making it feasible for on-field calibration.