A Fusion Approach for Image-Based Measurement of Speed Over Ground

One essential task in automotive engineering is the estimation of the speed over ground of cars. This information - the velocity vector and the yaw rate is for example being used in the development process of chassis as well as in various driver assistance systems. As the reliability of these systems is directly coupled to the quality of the velocity measure, it is desirable to provide a robust and accurate velocity estimate based on disjunctive sensors. Therefore this paper describes a multisensor fusion approach to determine the velocity vector of a car over ground. Two image based sensors are used, that already provide information about the speed over ground and - very important for fusion - a measure for the current uncertainty in terms of variance. The presented combination of the measurements in a Kalman-filter decreases measurement uncertainties and increases availability and robustness