Abstract: Airborne cognitive radar uses priori clutter knowledge-aided adaptive technique to suppress the clutter. Thus, the authenticity and validity of clutter model has a great influence on the detection performance of airborne cognitive radar. Considering the characteristics of signal processing technologies in airborne cognitive radar, this paper designs a clutter modeling method based on the digital elevation model data. The new method extracts the terrain factors influencing the power spectrum of clutter from DEM data. By combining the geographical landscape theory with the terrain factors, the real landforms provided by DEM are quantifiably classified. In order to increase the real-time in modeling clutter, a dynamic database is designed to store the quantized landform information. Finally, the ground clutter model is constructed based on the topography information and backscattering coefficient model. The simulation results show that the ground clutter model we constructed fits with the actual topography where the airborne radar locates. The model has the real, stable and reliable advantages when it is used to obtain the priori information of airborne cognitive radar and it can effectively aid airborne cognitive radar to improve detection performance and survivability.