# Fingerprints of the Automotive Radar Scattering of Passenger Cars and Vans
## 4 Conclusions  
The aim of this work was to analyze the scattering behavior of different vehicle types under certain drive scenarios. A special focus was placed on the influence of underbody detections caused by multipath propagation via the road surface. In the first part, microwave absorbers were used to show that reflections at the underbody have a significant impact on the measured target detections. When comparing measurements for different vehicle types, significant differences in the number of detections, their spatial distributions, and their RCS values were revealed. Due to the limited sensor resolution, it was not always possible to assign all detection clusters unambiguously to specific vehicle components. However, the number of detections at different distances as well as the RCS distributions enabled a general comparison of the reflectivity of the underbody for different vehicles. It became apparent that the geometry of the underbody has a major and distinctive influence on the scattering characteristics. For example, significantly fewer detections were recorded for a battery-electric vehicle compared to similar vehicle types with a combustion engine, which is attributed to the absence of the exhaust system and the resulting flat underbody. In addition, significantly more detections and higher RCS values were measured for vehicles where, for example, the rear axle, wheel suspension or chassis frame are clearly visible.  
It is worth noting that the six vehicle types studied here represent only a small fraction of cars on public roads. Therefore, in the real world, a wide range of scattering characteristics is to be expected, depending on the vehicle design, powertrain concept, exhaust aftertreatment components, axle geometry and ground clearance. Depicting such differences in models presents a big challenge and requires complex simulation methods with detailed CAD models. A simpler and still relevant approach towards fingerprinting radar scattering of cars could be to group into types of vehicles (e.g., combustion vs. electric engine) and assign coarse reflectivities to the underbody using stochastic models.  
Due to the limited sensor resolution, it is expected that the influence of underbody detections will mainly be visible for certain incident angles, e.g., when following a vehicle in front in urban traffic or on highways. However, anticipating further improvements in sensor resolution, the influence of underbody detections is likely to become more  
Figure 10: Relative frequency (**top**) and median RCS values (**bottom**) of target detections in longitudinal direction \(x\) for the six vehicle types.  
important for other traffic scenarios as well, such as at intersections. The ability to detect and characterize parts of the underbody is a unique characteristic of radar sensors and differentiates them from other sensor principles. Therefore, the systematic analysis of radar scattering is important to evaluate the possibility of improving the performance of automated driving functions.  
Formal analysis, P.A.; Investigation, P.A.; Methodology, P.A.; Project administration, F.H.; Supervision, J.D. and M.A.H.; Validation, P.A.; Visualization, P.A.; Writing--original draft, P.A.; Writing--review & editing, P.A., F.H. and M.A.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the German Federal Ministry for Education and Research (BMBF) under the project acronym VIVID with grant number 16 ME0172.  
Not applicable.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} SAR & synthetic aperture radar \\ RCS & radar cross section \\ \end{tabular}