Clutter Simulation for Four Common Distributions

This clutter simulation program implements four common statistical distributions: Gaussian, Rayleigh, Rician, and Weibull. The simulations are computed using coherent correlation simulation methodology, a computational technique designed to replicate real-world system phenomena through digital simulation. The implementation employs correlation-based algorithms that maintain phase coherence throughout the simulation process, ensuring accurate representation of temporal and spectral characteristics. The detailed procedural steps for the coherent correlation simulation approach are documented in the accompanying Word file, which includes comprehensive guidance on parameter selection and configuration, analysis methodologies for output results, and interpretation frameworks for simulated data. Key computational aspects involve covariance matrix generation for correlation modeling and inverse transform sampling for distribution realization. Users can select appropriate distributions and parameters based on specific application requirements. The code architecture allows flexible parameter adjustment through modular input interfaces, enabling precise control over simulation characteristics such as clutter intensity, spatial correlation, and statistical properties. The object-oriented design facilitates easy extension to additional distributions while maintaining computational efficiency through optimized matrix operations and vectorized processing.