K-Distribution Sea Clutter Simulation Program with MATLAB Implementation

The k-distribution method represents a statistical modeling approach for electromagnetic radiation transmission through non-homogeneous media like the atmosphere or sea surface. This technique finds significant applications in remote sensing, atmospheric radiation studies, and radar signal processing for sea clutter characterization. The MATLAB implementation enables realistic simulation of k-distributed sea clutter through key computational components: - Statistical parameter estimation for shape and scale factors governing the distribution - Correlated gamma-distributed texture generation using autoregressive processes - Compound distribution formation combining speckle and texture components - Phase randomization techniques for complex clutter signal generation Algorithm implementation involves: 1. Initializing distribution parameters (shape parameter ν, scale parameter θ) 2. Generating correlated gamma sequences using Cholesky decomposition of covariance matrices 3. Applying multiplicative noise models to create compound k-distribution 4. Implementing inverse transform sampling for random variate generation 5. Validating results through statistical moment comparisons and probability plots Core MATLAB functions include: - `kdist_param_est()` for parameter estimation from empirical data - `corr_gamma_gen()` producing correlated gamma sequences - `kdist_rv()` generating k-distributed random variables - `clutter_sim()` main simulation function with configurable parameters This simulation framework allows researchers to model electromagnetic radiation behavior in maritime environments, enabling accurate prediction of radar performance under various sea conditions. The method's statistical robustness and computational efficiency make it particularly valuable for atmospheric science, remote sensing applications, and telecommunications system design. The MATLAB code architecture features modular design with configurable parameters, comprehensive documentation, and validation routines ensuring reliable performance across different operational scenarios.