Simulation of Radar Clutter Model with Weibull Distribution and Gaussian Power Spectrum

In this technical implementation, we simulate radar clutter using a comprehensive model that incorporates Weibull distribution properties with Gaussian power spectrum characteristics. The simulation approach involves generating clutter samples through statistical distribution modeling where the Weibull distribution parameters (shape and scale) define the amplitude characteristics, while the Gaussian spectrum determines the frequency domain behavior. Algorithm implementation typically includes generating correlated sequences using autoregressive processes or spectral factorization methods to achieve the desired Gaussian spectral shape. Key functions in the simulation may involve probability density function calculations for Weibull distribution, Fast Fourier Transform operations for spectral analysis, and correlation techniques for temporal coherence. This simulation methodology enables thorough investigation of clutter properties under various parameter configurations, allowing researchers to analyze how different distribution parameters and spectral characteristics impact radar performance metrics. The implementation facilitates prediction and optimization of radar system behavior in diverse clutter environments, contributing significantly to system design refinement and performance validation. Through comprehensive simulation and parameter sensitivity analysis, we gain deeper insights into clutter behavior patterns, ultimately enhancing radar system effectiveness and operational reliability in practical scenarios.