基于Pareto 杂波的参数估计范围研究

当雷达工作在高海情环境时,相比于K分布模型,Pareto 分布是一种优势更大的统计杂波模型。基于Pareto杂波模型的参数估计研究,一直存在着参数估计表达式不闭合以及参数估计范围受限的问题,该文利用了正数阶矩估计的方法,不仅得到了闭合的估计表达式,而且扩大了参数估计的范围。同时,提出了负数阶矩估计,使参数估计的范围覆盖到参数的整个取值区间。实验表明,负数阶矩估计法运算速度快,估计范围不受限。与传统的估计法相比,参数取值越小,负数阶矩估计的估计性能越好,并且估计精度呈指数趋势提高。

A Study on Parameter Estimation Range Based on Pareto Clutter

Compared with K distribution model, the Pareto distribution is a dominant statistical clutter model when radar works in the Haitian environment. Based on the parameter estimation of Pareto clutter model, the estimation expression is not closed, and the range of parameter estimation is limited. Therefore, this paper utilizes the method of positive order estimation, which not only obtains the closed estimation expression, but also extends the range of parameter estimation. On this basis, the negative order moment estimation is further proposed, and the range of parameter estimation is covered by the whole range of parameter. The experiment shows that the calculation speed of negative order moment estimation is fast, and the range of parameter estimation is not limited. Compared with the traditional estimation methods, the smaller the parameter is, the better the estimation performance of negative order moment estimation is, and the accuracy of estimation is exponentially higher.