A method for extending the detection range of a short-range sensor, wherein the method comprises a first sensor setup for a production vehicle, comprising: - a short-range sensor, - a long-range auxiliary sensor which provides an anchor point measurement, and a second sensor setup for a training vehicle, comprising: - a short-range sensor, - a long-range auxiliary sensor which provides an anchor point measurement, - a long-range ground truth sensor, wherein the sensors of the first and second sensor setup having a sensor range and providing sensor data for reflection detection, the range extension is done with a neural network, wherein the neural network is trained using the following steps: - Detecting reflections (20, 21, 22) in the surrounding of the training vehicle by using sensor data of the second sensor setup - Determining an anchor point of a reflection which is out of a detection range of the short-range sensor of the second sensor setup by using the anchor point measurement of the long-range auxiliary sensor of the second sensor setup, - Providing ground truth by determining the distances (25, 33) between the anchor point and the other reflections (20, 22) by using the sensor data of the long-range ground truth sensor, and the method is executed on basis of the neural network using the following steps - Detecting reflections (20, 21, 22) in the surrounding of the production vehicle by using sensor data of the first sensor setup, - Determining anchor points of a reflection (20, 21) by using the anchor point measurement of the long-range auxiliary sensor of the first sensor setup, - Determining the distances between the anchor points and other reflections in the detection range of the short-range sensor of the first sensor setup by using the sensor data of the short-range sensor of the first sensor setup, and - Inferring the distances between the anchor points and other reflections out of the detection range of the short-range sensor of the first sensor setup by using the provided ground truth of the trained neural network. a first sensor setup for a production vehicle, comprising: - a short-range sensor, - a long-range auxiliary sensor which provides an anchor point measurement, and - a short-range sensor, - a long-range auxiliary sensor which provides an anchor point measurement, and a second sensor setup for a training vehicle, comprising: - a short-range sensor, - a long-range auxiliary sensor which provides an anchor point measurement, - a long-range ground truth sensor, wherein - a short-range sensor, - a long-range auxiliary sensor which provides an anchor point measurement, - a long-range ground truth sensor, wherein the sensors of the first and second sensor setup having a sensor range and providing sensor data for reflection detection, the range extension is done with a neural network, wherein the neural network is trained using the following steps: - Detecting reflections (20, 21, 22) in the surrounding of the training vehicle by using sensor data of the second sensor setup - Determining an anchor point of a reflection which is out of a detection range of the short-range sensor of the second sensor setup by using the anchor point measurement of the long-range auxiliary sensor of the second sensor setup, - Providing ground truth by determining the distances (25, 33) between the anchor point and the other reflections (20, 22) by using the sensor data of the long-range ground truth sensor, and - Detecting reflections (20, 21, 22) in the surrounding of the training vehicle by using sensor data of the second sensor setup - Determining an anchor point of a reflection which is out of a detection range of the short-range sensor of the second sensor setup by using the anchor point measurement of the long-range auxiliary sensor of the second sensor setup, - Providing ground truth by determining the distances (25, 33) between the anchor point and the other reflections (20, 22) by using the sensor data of the long-range ground truth sensor, and the method is executed on basis of the neural network using the following steps - Detecting reflections (20, 21, 22) in the surrounding of the production vehicle by using sensor data of the first sensor setup, - Determining anchor points of a reflection (20, 21) by using the anchor point measurement of the long-range auxiliary sensor of the first sensor setup, - Determining the distances between the anchor points and other reflections in the detection range of the short-range sensor of the first sensor setup by using the sensor data of the short-range sensor of the first sensor setup, and - Inferring the distances between the anchor points and other reflections out of the detection range of the short-range sensor of the first sensor setup by using the provided ground truth of the trained neural network. - Detecting reflections (20, 21, 22) in the surrounding of the production vehicle by using sensor data of the first sensor setup, - Determining anchor points of a reflection (20, 21) by using the anchor point measurement of the long-range auxiliary sensor of the first sensor setup, - Determining the distances between the anchor points and other reflections in the detection range of the short-range sensor of the first sensor setup by using the sensor data of the short-range sensor of the first sensor setup, and - Inferring the distances between the anchor points and other reflections out of the detection range of the short-range sensor of the first sensor setup by using the provided ground truth of the trained neural network.