In the field of mobility, the importance of intelligent driver assistance systems and autonomous vehicles will increase steadily in the future. In order to be able to develop the systems required for this, the automotive industry is dependent on corresponding sensor technology that is capable of reliably recording the environment of a vehicle in real time and providing the system with relevant information about the dynamic traffic scene at the decision-making level. The use of radar sensors has decisive technological advantages over other environment sensors, since in addition to the weather-independent environment detection, information about movement and relative relative speeds of objects can be captured. Until now, radar sensors as well as decision-level algorithms have had to be validated with time-consuming test drives. As part of a research project, Fraunhofer FHR has developed a simulation method embedded in a software environment that can be used to synthesize raw radar data from a virtual traffic scene. Furthermore, a radar target simulator has been developed at FHR, with which the radar raw data can be played back to the radar sensors over-the-air after further processing to object lists.