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涂覆吸波材料圆柱的RCS预估方法
引用本文:赵京城,杨宗凯,王健,张扬.涂覆吸波材料圆柱的RCS预估方法[J].北京航空航天大学学报,2021,47(7):1362-1371.
作者姓名:赵京城  杨宗凯  王健  张扬
作者单位:1.北京航空航天大学 电子信息工程学院, 北京 100083
摘    要:用缩比模型测量结果预估是研制阶段获得大尺寸目标雷达散射截面(RCS)的常用方法,但根据经典电磁相似理论,严格满足缩比条件的涂覆吸波材料缩比目标测量难以实现。针对涂覆吸波材料缩比目标的RCS预估问题,提出了采用多元对数线性回归模型的预估方法。设计了2组圆柱模型,在微波暗室中对缩比因子分别为1、2、4、8的2组模型进行了测试。在完成角度矫正等数据预处理基础上,将缩比模型RCS数据作为训练集代入模型当中求得参数,对原模型的RCS进行预估并与实际实测数据进行对比分析。结果表明:所提方法预估数据与实测数据曲线拟合度较好,相较于传统平方率模型,误差下降了3~5 dB,在回归模型中加入吸波材料因子后误差进一步下降了0.3~0.8 dB。 

关 键 词:雷达散射截面(RCS)    缩比模型    多元线性回归    吸波材料    相似原理
收稿时间:2020-05-25

RCS prediction method for cylinder containing microwave absorbing material
ZHAO Jingcheng,YANG Zongkai,WANG Jian,ZHANG Yang.RCS prediction method for cylinder containing microwave absorbing material[J].Journal of Beijing University of Aeronautics and Astronautics,2021,47(7):1362-1371.
Authors:ZHAO Jingcheng  YANG Zongkai  WANG Jian  ZHANG Yang
Institution:1.School of Electronic and Information Engineering, Beihang University, Beijing 100083, China2.AVIC The First Aircraft Institute, Xi'an 710089, China
Abstract:Large target's Radar Cross Section (RCS) estimation using scaling model is a common method to obtain RCS at the development phase. However, according to classical electromagnetic similarity theory, measurement of scaled target coated with microwave absorbing material is difficult to meet the scaling condition strictly. A multivariate logarithmic linear regression model is proposed to estimate RCS for the scaled target coated with microwave absorbing materials. Two sets of cylindrical models were designed and tested in the microwave anechoic chamber with scaling factors of 1:1, 1:2, 1:4 and 1:8, respectively. On the basis of data preprocessing such as angle correction, RCS data of scaling model is substituted into the model as training set to obtain parameters, and RCS of the original model is estimated and compared with the actual measured data. The results show that the curves of the predicted data and the measured data fit well. Compared with the traditional square rate formula, the error of the proposed method decreases by 3-5 dB, and the error decreases by 0.3-0.8 dB after adding the microwave absorbing material factor to the regression model. 
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