The modeling and analysis of sea clutter are of great significance in radar target detection studies in marine environments. Sea clutter typically exhibits non-Gaussian characteristics and spatiotemporal correlations, posing challenges for modeling, especially when generating simulation data of continuous correlated non-Gaussian random processes. This paper proposes a novel method for sea clutter modeling. First, feature description functions are constructed to individually characterize the amplitude, temporal, and spatial correlations of sea clutter, allowing for an accurate depiction of its characteristics with fewer parameters. Subsequently, simulation data are generated based on these feature description functions, satisfying the amplitude distribution, temporal correlation, and spatial correlation characteristics of sea clutter. Additionally, complex signal forms are introduced in the underlying signal processing to generate texture and speckle components of sea clutter, enhancing the alignment of simulation data with actual data. Through comparison with measured sea clutter data, the proposed method has been shown to accurately simulate complex sea clutter with real-world characteristics.