涂覆吸波材料圆柱的RCS预估方法

赵京城; 杨宗凯; 王健; 张扬

doi:10.13700/j.bh.1001-5965.2020.0214

涂覆吸波材料圆柱的RCS预估方法

doi: 10.13700/j.bh.1001-5965.2020.0214

赵京城^1, ,,
杨宗凯¹,
王健²,
张扬²

1.
北京航空航天大学电子信息工程学院, 北京 100083
2.
航空工业第一飞机设计研究院, 西安 710089

详细信息

通讯作者:
赵京城. E-mail: zjccool@126.com

中图分类号: TN951
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- 被引次数: 0
出版历程
- 收稿日期: 2020-05-25
- 录用日期: 2020-08-01
- 网络出版日期: 2021-07-20

RCS prediction method for cylinder containing microwave absorbing material

1.
School of Electronic and Information Engineering, Beihang University, Beijing 100083, China
2.
AVIC The First Aircraft Institute, Xi'an 710089, China

More Information

Corresponding author: ZHAO Jingcheng. E-mail: zjccool@126.com

摘要

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。
- 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
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.
- Radar Cross Section (RCS) /
- scaling model /
- multiple linear regression /
- microwave absorbing material /
- similarity principle

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图 1 吸波材料反射率随频率变化

Figure 1. Reflectance of microwave absorbing materials varies with frequency

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图 2 测试场地示意图

Figure 2. Sketch map of test site

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图 3 两种圆柱模型的设计图

Figure 3. Design drawing of two kinds of cylinder model

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图 4 实际测试示意图

Figure 4. Sketch map of actual test

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图 5 测试及数据处理流程

Figure 5. Flowchart of test and data processing

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图 6 测试频率1.835 GHz下圆柱1单站RCS对角度曲线

Figure 6. Influence of angle on cylinder 1's monostatic RCS with test frequency of 1.835 GHz

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图 7 不同缩比因子模型的角度偏差统计对比

Figure 7. Comparison of angle deviation of models with different scaling factors

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图 8 圆柱1不同模型下单站RCS预估与实测对比

Figure 8. Comparison of prediction and measurement of cylinder 1's monostatic RCS in different models

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图 9 圆柱2不同模型下单站RCS预估与实测对比

Figure 9. Comparison of prediction and measurement of cylinder 2's monostatic RCS in different models

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表 1 电磁相似原理条件

Table 1. Conditions of electromagnetic similarity principle

物理量	原模型	缩比模型
长度	l	l′=l/n
频率	f	f′=nf
波长	λ	λ′=λ/n
电导率	σ	σ′=nσ
磁导率	μ	μ′=μ
介电常数	ε	ε′=ε
表面阻抗	η	η′=η

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表 2 圆柱1的尺寸及测试频率

Table 2. Dimension and test frequency of cylinder 1

n	长度/mm	直径/mm	测试频率/GHz	组数
0.96	2 092	159	1.5~2	101
2	1 000	76	3.5~4.5	201
4	500	38	7~9	401
8	250	19	14~18	801

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表 3 圆柱2的尺寸及测试频率

Table 3. Dimension and test frequency of cylinder 2

n	长度/mm	直径/mm	测试频率/GHz	组数
1	480.0	240	2~2.5	101
2	240	120	3.5~4.5	201
4	120	60	7~9	401
8	60	30	14~18	801

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表 4 测量误差与目标和背景电平的差值典型数据

Table 4. Typical data of measurement error according to difference of target and background ratio

	测量误差/dB
31	±0.25
25	±0.5
19	±1
16	±1.5
10.69	±3

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表 5 圆柱1数据角度校准结果

Table 5. Calibration results of angle of cylinder 1 (°)

极化方式	n=0.96	n=2	n=4	n=8
HH	-0.6	0.2	-0.2	-0.2
VV	-0.6	0	-0.2	0.4

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表 6 圆柱2数据角度校准结果

Table 6. Calibration results of angle of cylinder 2 (°)

极化方式	n=1	n=2	n=4	n=8
HH	0.2	0.2	0.2	0.8
VV	0	0.2	0.4	-0.2

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表 7 圆柱1的模型1摘要(HH极化)

Table 7. Model one's summary of cylinder 1(HH polarization)

R	R²	调整后的R²	标准估算的误差
0.980	0.961	0.961	1.602 808

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表 8 圆柱1的模型1回归方程系数(HH极化)

Table 8. Model one's regression equation coefficients of cylinder 1 (HH polarization)

因子	系数	标准错误	t	显著性
x₁	0.943	0	2 830.873	0
x₂	27.175	0.041	967.286	0

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表 9 圆柱1不同模型回归公式与平均绝对误差对比

Table 9. Comparison of regression formula and absolute error of cylinder 1 in different models

极化方式	模型	回归公式	相关系数	拟合度	平均绝对误差/dB
HH极化	传统平方率模型	y=x₁+20x₂	0.927	0.859	4.93
HH极化	模型1	y=0.943x₁+27.175x₂	0.980	0.961	1.94
HH极化	模型2	y=0.996x₁+21.279x₂-0.08x₃-0.708x₄	0.998	0.995	1.11
VV极化	传统平方率模型	y=x₁+20x₂	0.934	0.872	5.26
VV极化	模型1	y=0.991x₁+30.630x₂	0.992	0.984	2.14
VV极化	模型2	y=1.039x₁+19.476x₂-1.728x₃-0.378x₄	0.994	0.988	1.29

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表 10 圆柱2不同模型回归公式与平均绝对误差对比

Table 10. Comparison of regression formula and absolute error of cylinder 2 in different models

极化方式	模型	回归公式	相关系数	拟合度	平均绝对误差/dB
HH极化	传统平方率模型	y=x₁+20x₂	0.934	0.872	7.18
HH极化	模型1	y=0.969x₁+33.130x₂	0.996	0.992	2.30
HH极化	模型2	y=0.964x₁+26.455x₂+0.355x₃-0.483x₄	0.997	0.995	1.62
VV极化	传统平方率模型	y=x₁+20x₂	0.946	0.895	5.92
VV极化	模型1	y=1.005x₁+30.119x₂	0.989	0.979	2.41
VV极化	模型2	y=0.969x₁+19.469x₂+0.046x₃-0.894x₄	0.991	0.982	2.18

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