Abstract: During aircraft oversea flight, strong and widespread sea clutter can severely interfere with the correct identification of meteorological echoes. The amplitude statistical characteristics of sea clutter are crucial for the detection of meteorological targets. To accurately evaluate the amplitude statistical characteristics of sea clutter and thus effectively suppress it, this paper proposes a distribution model parameter estimation method based on the interior point algorithm. This method transforms the problem of estimating the parameters of high-order sea clutter statistical curves into sub-problems for solving the optimal solution, enabling rapid search and estimation of sea clutter amplitude distribution parameters. Furthermore, a new adaptively adjusted objective function is introduced to enhance the fitting effect of the distribution model and the measured clutter in the tail part. Combining the statistical characteristics of measured sea clutter data from shore-based multi-band radars under different sea states and radar parameters, and through a comparative analysis with typical parameter estimation and optimization methods, it can be seen that the method in this paper can achieve a better estimation of the measured sea clutter amplitude distribution parameters, and the fitting effect of the amplitude distribution curve at the tail is better. Through a comparative statistical analysis of the measured clutter data under different conditions, the universality of this parameter estimation method is verified. Experimental data show that the fitting accuracy improvement rate reaches 70% in the case of K-distribution.