Approaches and landing maneuvers are some of the most critical tasks in aviation. Especially under adverse weather conditions (when the runway can't be seen) pilots need additional information about the relative position between runway and aircraft. In this paper, we present a system, which provides such navigation information based on the analysis of millimeter wave (MMW) radar data. The advantage of MMW radar sensors is that the data acquisition is independent from the actual weather and daylight situation. The core part of the presented system is a fuzzy rule based inference machine, which controls the data analysis based on the uncertainty in the actual knowledge in combination with a-priori knowledge. Compared with standard TV or IR images the quality of MMW images is rather poor and data is highly corrupted with noise and clutter. Therefore, one main task of the inference machine is to handle uncertainties as well as ambiguities and inconsistencies to draw the right conclusions. The performance of our approach is demonstrated with real data acquired during extensive flight tests to several airports in Northern Germany.