Frequency modulated continuous wave (FMCW) mmWave radar has become a key sensor in many advanced driver assistance systems (ADAS). Due to its excellent range and Doppler resolution, it is an attractive sensor for detecting and tracking vulnerable road users such as cyclists and pedestrians. Although tracking algorithms such as Kalman or Particle Filters have been well established, it is still challenging to quickly and accurately estimate the position and velocity of a (new) object from a limited number of (noisy) radar detections. In order to assess the performance of such estimation strategies, we derive the Cramer-Rao lower bound (CRLB) for position and velocity estimation, based on successive radar measurements of an object's range, azimuth, and relative radial velocity.