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This paper will examine the impact of discrete clutter on airborne adaptive radar systems using a hi-fidelity radar cross section (RCS) model of buildings. A realistic model of the RCS for different building designs with respect to incidence angle and operating frequency has been developed that captures the phenomenology necessary to study the impact of discrete clutter on adaptive signal processing algorithms. A key aspect of the RCS model is that it captures the key phenomenology while maintaining computational efficiency so it can readily be used in existing high-fidelity clutter simulations. Through the use of experimental data, we present examples of how the strong radar returns from buildings impact the performance of space-time adaptive processing (STAP). Validation of the RCS model against experimental data indicates its potential role in knowledge-aided clutter mitigation techniques to improve STAP performance.