基于频域稀疏压缩感知的雷达目标三维散射中心反演方法

doi:10.12305/j.issn.1001-506X.2022.09.11

摘要/Abstract

摘要：

基于平面阵列的微波天线结构可以获取多视角下的目标散射中心三维分布。针对平面阵列稀疏分布导致的目标成像及散射中心反演精度较差的问题, 设计了一种基于组合巴克码的稀疏孔径分布方式。在此基础上, 利用稀疏孔径回波和频域主成分分析得到参考复数信号。利用该参考复数信号对原始回波进行干涉处理, 获得回波频谱的稀疏表征方式。在频域建立基于压缩感知的目标散射中心三维分布模型并进行优化求解, 得到重构后的目标三维频谱, 并逆变换至空间域, 可实现目标散射中心幅度及三维位置重建。暗室试验数据处理结果表明, 所提方法在X波段和稀疏采样率为50%的条件下, 目标散射中心幅度及三维位置反演精度均优于90%。

关键词: 稀疏孔径, 主成分分析, 压缩感知, 三维图像重建

Abstract:

The microwave antenna structure based on planar array has the ability to obtain the three-dimensional (3D) distribution of scattering centers on observed object under multi-angles. To improve the poor accuracy of imaging and scattering center inversion caused by the sparse aperture distribution in planar array, a sparse aperture distribution method based on combined Barker sequence is designed. We use sparse aperture echo and principal component analysis (PCA) of frequency domain to get referential complex signals. Then the interferometry is implemented between the original echo and the referential complex signal, and the sparse representation of the echo spectrum is acquired. The 3D distribution model of the target scattering center based on compressed sensing (CS) is established in the frequency domain, and the optimization algorithm is employed to solve the model and obtain the reconstructed 3D spectrum of the target. By inverse transformation to the spatial domain, the reconstruction of the amplitude and 3D position of the target scattering center are realized. The result of experimental data of the anechoic chamber verifies that under the condition of X-band and sparse sampling rate of 50%, the proposed method has a 3D location extraction accuracy of above 90%.

Key words: sparse aperture, principal component analysis (PCA), compressed sensing (CS), three-dimensional (3D) image reconstruction

中图分类号:

TN959.74

田鹤, 董纯柱, 殷红成. 基于频域稀疏压缩感知的雷达目标三维散射中心反演方法[J]. 系统工程与电子技术, 2022, 44(9): 2783-2790.

He TIAN, Chunzhu DONG, Hongcheng YIN. Radar target three-dimensional scattering centers inversion based on compressed sensing and frequency sparsity[J]. Systems Engineering and Electronics, 2022, 44(9): 2783-2790.

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参数名称	参数数值
工作波长/m	0.03
观测距离/m	1.60
信号带宽/GHz	4
天线扫描面大小/m²	1.00×1.00
X方向采样点数	51
Y方向采样点数	51
Z方向采样点数	201
X方向分辨率/m	0.026 6
Y方向分辨率/m	0.026 6
Z方向分辨率/m	0.037 5

算法	评价指标
算法	相关系数	RMSE/m	SSIM
匹配滤波	0.652 7	0.199 5	0.867 4
PCA+CS	0.909 6	0.106 7	0.962 1
CS	0.873 4	0.123 3	0.922 0
LPF	0.801 2	0.158 7	0.900 1

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