典型隐身飞机的RCS起伏统计特性
收稿日期: 2013-12-30
修回日期: 2014-04-14
网络出版日期: 2014-05-07
Radar Cross Section Fluctuation Characteristics of Typical Stealth Aircraft
Received date: 2013-12-30
Revised date: 2014-04-14
Online published: 2014-05-07
雷达散射截面(RCS)起伏统计特性可以用来预测雷达的检测性能和评估飞机的散射特性.采用高频计算方法获取了6种典型隐身飞机在光学区8个频率点、两种极化方式、不同入射条件下的周向RCS统计数据.应用3种较新的起伏模型对统计数据进行拟合,通过对比分析各组数据的拟合效果,得出了各模型在数据拟合时存在的普遍规律:卡方(Chi-square)模型对概率密度分布曲线的峰值估计较为合理,对数正态模型容易将峰值高估,但在峰值之后卡方模型的拟合效果通常不如对数正态模型;统计数据均值的平方与方差之比越大(可达0.1~1.0),则卡方模型双自由度越大(可达1.1~1.5),拟合效果也越好,按Kolmogorov-Smirnov检验方法其误差在0.15~0.25范围内;统计数据的均值中值比越小(低至1.5~5.0),则对数正态模型拟合效果越好,误差在0.01~0.25范围内;在dB·m2单位制下,采用对数正态模型和勒让德多项式模型可以在更广的范围内更好地拟合各组数据,其拟合误差多在0.10以下.
陈世春 , 黄沛霖 , 姬金祖 . 典型隐身飞机的RCS起伏统计特性[J]. 航空学报, 2014 , 35(12) : 3304 -3314 . DOI: 10.7527/S1000-6893.2014.0053
Radar cross section (RCS) fluctuation characteristics are used to predict radar's detection performance and evaluate aircraft's scattering characteristic. Azimuth RCS statistics under different incident conditions for six typical stealth aircraft at eight different bands each with two kinds of polarizations are obtained utilizing high-frequency electromagnetic computation method. Three kinds of relatively new fluctuation models are used to fit those statistics and some universal conclusions are made by analyzing all the fitting patterns. The Chi-square model gives a better peak value estimation for the probability density distribution curve but doesn't fit very well after the curve peak; the log-normal model often gives a higher estimation for the peak value but fits well after the curve peak; the fitting error of Chi-square model decreases when the double-degrees of freedom increases (to about 1.1-1.5), which results from the increasing ratio (about 0.1-1.0) of the mean square to the variance of the statistics, and according to the Kolmogorov-Smirnov testing method, the error is about 0.15 to 0.25; the fitting error of log-normal model also decreases (to about 1.5-5.0) when the ratio of mean to median value of the statistics decreases. When the statistics unit is dB·m2, the log-normal model and Legendre polynomials model always fit the data well more widely and the error is generally lower than 0.10.
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