Analysis and Fitting of Scattering Characteristics Distribution of Different Terrains in the Terahertz Frequency Range

In the terahertz frequency range, radar imaging technology holds significant potential for widespread applications in surface monitoring and target detection. This study aims to conduct an analysis of radar imaging results from four distinct scenarios, namely agricultural fields, road surfaces, lake surfaces, and urban areas. For the radar imaging data corresponding to these diverse scenarios, we employed mathematical models to fit their histograms. The fitting process considered various models such as Generalized Gaussian Distribution (GGD), Gamma distribution, Rayleigh distribution, and Rice distribution. These models exhibit different advantages in describing data distribution, and the most suitable model was determined through a comparative analysis of their fitting performances. To assess the accuracy of the fitting and the adaptability of the models, we computed determination coefficients and root mean square errors. These metrics were utilized to evaluate fitting precision and model adaptability, facilitating meaningful comparisons. The findings indicate that histograms of radar imaging exhibit varying characteristics across different scenes, necessitating the use of different models for fitting. The research findings play a crucial role in various radar applications, encompassing a broad spectrum from target identification to image enhancement.