基于高斯混合密度模型的隐身目标RCS统计分析

为克服传统RCS起伏统计模型描述隐身目标起伏特性的不足,提出了一种将高斯混合密度模型(GMDM)应用于RCS统计分析的建模方法。根据典型隐身目标的仿真数据,分别建立了该目标在不同方位角范围内的2阶GMDM和χ2分布模型。拟合结果表明2阶GMDM在前侧向、正侧向和后侧向拟合误差分别为4.74%、12.34%和1.01%,而χ2模型的拟合误差分别为44.5%、18.65%和13.21%。同时,当拟合阶数超过4阶时,GMDM的拟合误差将稳定在5%以下,能够满足雷达目标仿真的精度需求。

A Statistical Analysis of Radar Targets' RCS Based on GMDM

In order to overcome the inadequacy of conventional RCS statistical models describing stealth target fluctuation, a new RCS statistical modeling method based on Gaussian mixture density model is presented. The two-order GMDM and distribution model are established respectively based on the simulation data of typical stealth target. The results show that the forward, side and backward fitting errors of GMDM are respectively 4.74%, 12.34% and 1.01%, while those of the model are 44.5%, 18.65% and 13.21%. And simultaneously when fitting order in number exceeds four-order, the fitting error of GMDM remains below 5% steadily, which can satisfy the precision demand of radar target simulation.