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Adverse weather conditions affect flight safety as well as efficiency of airport operations. The problem becomes evident in critical flight phases such as approach, landing, take-off, and taxiing so that the nominal airport capacity has to be reduced during low visibility conditions due to safety concerns. Hence, DLR's Institute of Flight Guidance has conducted a lot of research work in the field of enhanced and synthetic vision to overcome these problems by improving pilot's visual perception. Data acquired by weather penetrating sensors are combined with digital terrain data and status information by application of data fusion techniques. The resulting description of the situation is given to the pilot via head-up or head-down displays. This contribution is focused on the automatic analysis of millimeter wave (MMW) radar images with regard to the requirements for a sensor based landing. Compared to standard TV or IR images, the quality of the radar data is quite poor. Therefore, the handling of uncertainties is a core element of the presented methods. The uncertainties are modeled with fuzzy sets.