基于IRLS的跳频模式下GTD散射参数提取和RCS重构

doi:10.12305/j.issn.1001-506X.2023.03.08

摘要/Abstract

摘要：

现代谱估计方法能够反演基于几何绕射理论(geometric theory of diffraction, GTD)的模型参数, 但不能处理非均匀不完备的雷达散射截面(radar cross section, RCS)数据。此外, 通过暗室测量获取完备的RCS数据也需要较大的时空开销。针对上述问题, 提出一种基于迭代加权最小二乘(iteratively reweighed least squares, IRLS)的跳频模式下GTD散射参数提取和RCS重构方法。该方法将稀疏重构理论与GTD散射模型相结合, 能够在RCS数据非均匀不完备的条件下反演散射参数和实现RCS重构。仿真数据和电磁计算数据用于验证所提方法的有效性, 实验结果表明该方法对降低暗室步进频率RCS的测量成本和扩增雷达RCS数据具有重要意义。

关键词: 雷达散射截面重构, 散射参数提取, 几何绕射理论模型, 跳频模式, 迭代加权最小二乘算法

Abstract:

Modern spectral estimation methods can extract the scattering parameters based on the geometric theory of diffraction (GTD) model, but they cannot deal with non-uniform and incomplete radar cross section (RCS) data. Furthermore, obtaining complete RCS data in anechoic chambers requires large space-time cost. To solve these problems, an iteratively reweighed least squares (IRLS)-based method for GTD scattering parameter extraction and RCS reconstruction in frequency hopping mode is proposed. Combining the sparse reconstruction theory with the GTD scattering model, the proposed method can retrieve scattering parameters and realize RCS reconstruction under the condition of non-uniform and incomplete RCS data. Simulation data and electromagnetic calculation data are used to verify the effectiveness of the proposed method. And the experimental results indicate that the proposed method is significant to reduce the cost of stepped-frequency RCS measurement in anechoic chambers and expand RCS data in database.

Key words: radar cross section (RCS) reconstruction, scattering parameter extraction, geometric theory of diffraction (GTD) model, frequency hopping mode, iteratively reweighed least squares (IRLS) algorithm

中图分类号:

TP957

李英俊, 刘永祥, 田彪, 张文鹏. 基于IRLS的跳频模式下GTD散射参数提取和RCS重构[J]. 系统工程与电子技术, 2023, 45(3): 678-689.

Yingjun LI, Yongxiang LIU, Biao TIAN, Wenpeng ZHANG. GTD scattering parameter extraction and RCS reconstruction in frequency hopping mode based on IRLS[J]. Systems Engineering and Electronics, 2023, 45(3): 678-689.

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典型散射类型	α取值
二面角反射、三面角反射、平板反射	1
单曲面反射、圆柱面反射	0.5
点散射、双曲面反射	0
边缘绕射	-0.5
尖顶绕射	-1

散射中心	r/m	A	α
S1	2.700	0.38+0i	0.5
S2	4.125	1+0i	0
S3	4.237 5	0.586+0i	0.5
S4	4.950	0.414+0i	1

稀疏度ρ/%	散射中心	r/m	A	α
100.0	S1	2.700 0	0.380 4-0.001 4i	0.500 0
	S2	4.128 5	0.992 2-0.002 4i	0.020 0
	S3	4.236 8	0.577 4+0.015 0i	0.480 0
	S4	4.950 0	0.413 6-0.000 5i	1.000 0
50.0	S1	2.700 0	0.378 7+0.000 0i	0.500 0
	S2	4.125 1	1.005 4-0.002 9i	0.020 0
	S3	4.238 3	0.576 3-0.007 6i	0.531 3
	S4	4.950 0	0.414 4-0.002 0i	1.000 0

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[4]	郑舒予, 张小宽, 宗彬锋. 基于改进MUSIC算法的散射中心参数提取及RCS重构[J]. 系统工程与电子技术, 2020, 42(1): 76-82.