An Effective Probabilistic Model for Clutter Signal Representation

The clutter distribution contributes to the design of the radar system. The matching distribution model improves the performance of the system. Several research papers investigate the performance of the classical distributions for alternative environmental scenarios. A few researchers introduced a better-performing model to fit the cluttering under the general application. The specific application of the distribution model requires a pre-processing stage to ensure its success. This paper introduces the statistical model to represent clutter returns for general ground surfaces. In particular, the introduced model extracts the parameters from the clutter returns, increasing the model’s performance. The performance of the proposed model was evaluated and compared with the classical statistical distributions such as the Rayleigh, Weibull, Lognormal etc., using the performance measures of root mean squared error (RMSE), relative error (RE), and R2. The exitance of the statistical model was proved mathematically and used the well know Kolmogorov–Smirnov (K-S) test for the fitness test. The presented model has outperformed all classic models.