Comprehensive situation awareness is very important for aircrews to handle complex situations like landing approaches or taxiing, especially under adverse weather conditions. Thus, DLR's Institute of Flight Guidance is developing an Enhanced Vision System that uses different forward looking imaging sensors to gain information needed for executing given tasks. Furthermore, terrain models, if available, can be used to control as well as to support the sensor data processing. Up to now, the most promising sensor due to its lowest weather dependency compared to other imaging sensors seems to be a 35 GHz MMW radar from DASA, Ulm, which provides range data with a frame rate of about 16 Hz. In previous contributions first experimental results of our radar data processing have been presented. In this paper we deal with radar data processing in more detail. Automatic extraction of relevant features for landing approaches and taxiing maneuvers will be focused. In the first part of this contribution we describe a calibration of the MMW radar which is necessary to determine the exact relationship between raw sensor data (pixels) and world coordinates. Furthermore, a calibration gives us an idea how accurate features can be located in the world. The second part of this paper is about our approach for automatically extracting features relevant for landing and taxiing. Improvements of spatial resolution as well as noise reduction are achieved with a multi frame approach. The correspondence of features in different frames is found with the aid of navigation sensors like INS or GPS, but can also be done by tracking methods. To demonstrate the performance of our approach we applied the extraction method on simulated data as well as on real data. The real data have been acquired using a test van and a test aircraft, both equipped with a prototype of the imaging MMW Radar from DASA, Ulm.