基于高斯混合密度模型的隐身目标RCS统计分析  

A Statistical Analysis of Radar Targets' RCS Based on GMDM

作　　者：庄亚强[1] 张晨新[1] 张小宽[1] 周超[1] 

机构地区：[1]空军工程大学防空反导学院,陕西西安710051

出　　处：《空军工程大学学报（自然科学版）》2014年第2期37-40,共4页Journal of Air Force Engineering University(Natural Science Edition)

基　　金：国家自然科学基金资助项目(61372166)

摘　　要：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。In order to overcome the inadequacy of conventional RCS statistical models describing stealth tar- get fluctuation, a new RCS statistical modeling method based on Gaussian mixture density model is pres- ented. 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 GM- DMare 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.

关 键 词：雷达散射截面 高斯混合密度模型 统计分析 拟合 

分 类 号：TN955.2[电子电信—信号与信息处理]