Synthetically generated radar imagery can provide a unique virtual environment which integrates the variability of sensor, scene, operational, and processing parameters. Since the advent of radar sensor technology, a significant level of effort has been expended on the development of electromagnetic modeling techniques to understand and predict the scattering and sensor phenomenology involved in synthetic-aperture radar (SAR) imaging systems. The inception of CAD/CAM tools in designing targets has allowed for the accurate prediction of geometrically and materially defined targets for use in signature prediction models. These three-dimensional target models are well suited for signature predictions which utilize deterministic approaches such as shooting/bouncing ray, finite-difference time-domain, and finite-element methods. In the area of clutter modeling, however, the temporal and inhomogeneous nature of foliage and terrain constituents require a hybrid formulation of deterministic and statistical approaches. In light of these modeling requirements, an effort to integrate sensor, target, and clutter simulations had led to the development of a SAR simulation system, advanced radar imaging emulation system (ARIES). This software provides the synthetic generation of high-fidelity SAR imagery for a wide range of user-defined platform, sensor, and scene parameters.