  Simulation-based testing is a promising approach to significantly reduce the
validation effort of automated driving functions. Realistic models of
environment perception sensors such as camera, radar and lidar play a key role
in this testing strategy. A generally accepted method to validate these sensor
models does not yet exist. Particularly radar has traditionally been one of the
most difficult sensors to model. Although promising as an alternative to real
test drives, virtual tests are time-consuming due to the fact that they
simulate the entire radar system in detail, using computation-intensive
simulation techniques to approximate the propagation of electromagnetic waves.
In this paper, we introduce a sensitivity analysis approach for developing and
evaluating a radar simulation, with the objective to identify the parameters
with the greatest impact regarding the system under test. A modular radar
system simulation is presented and parameterized to conduct a sensitivity
analysis in order to evaluate a spatial clustering algorithm as the system
under test, while comparing the output from the radar model to real driving
measurements to ensure a realistic model behavior. The presented approach is
evaluated and it is demonstrated that with this approach results from different
situations can be traced back to the contribution of the individual sub-modules
of the radar simulation.
