利用多通道联合稀疏重建的干涉逆合成孔径雷达三维成像算法

陈倩倩; 张磊; 徐刚; 邢孟道; 保铮

doi:10.7652/xjtuxb201412016

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利用多通道联合稀疏重建的干涉逆合成孔径雷达三维成像算法

更新时间：2025-07-09

- 利用多通道联合稀疏重建的干涉逆合成孔径雷达三维成像算法
- A Three-Dimensional Imaging Algorithm of Interferometric Inverse Synthetic Aperture Radar Using Multichannel Joint Sparse Recovery
- 西安交通大学学报 2014年48卷第12期页码：100-106
- 作者机构：
  
  西安电子科技大学雷达信号处理国家重点实验室,西安,710071
- 作者简介：
- 基金信息：
  
  : 2014-03-21。作者简介: 陈倩倩(1984—),女,博士生;邢孟道(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(61301280,61001211)
- DOI：10.7652/xjtuxb201412016
  中图分类号： TN957.52
- 网络首发：2014-12-10，
  
  纸质出版：2014
- 稿件说明：
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陈倩倩, 张磊, 徐刚, 等. 利用多通道联合稀疏重建的干涉逆合成孔径雷达三维成像算法[J]. 西安交通大学学报, 2014,48(12):100-106.

A Three-Dimensional Imaging Algorithm of Interferometric Inverse Synthetic Aperture Radar Using Multichannel Joint Sparse Recovery[J]. 2014, 48(12): 100-106.
陈倩倩, 张磊, 徐刚, 等. 利用多通道联合稀疏重建的干涉逆合成孔径雷达三维成像算法[J]. 西安交通大学学报, 2014,48(12):100-106. DOI： 10.7652/xjtuxb201412016.

A Three-Dimensional Imaging Algorithm of Interferometric Inverse Synthetic Aperture Radar Using Multichannel Joint Sparse Recovery[J]. 2014, 48(12): 100-106. DOI： 10.7652/xjtuxb201412016.

摘要

针对单通道超分辨成像算法重建的超分辨图像间散射点的位置出现偏差的问题

提出了一种利用多通道联合稀疏重建的干涉逆合成孔径雷达(MCJSR-InISAR)三维成像算法。首先利用联合包络对齐算法校正目标平动对应的包络时延

再利用联合自聚焦算法实现平动补偿的初相校正

对来自不同天线的回波信号的距离差进行补偿

然后利用MCJSR进行超分辨成像

同时利用快速傅里叶变换提高运算效率

最后利用水平及俯仰干涉相位信息实现机动目标的InISAR三维成像。MCJSR-InISAR算法具有更高的强散射中心重建精度

能够对通道间的相对相位信息进行有效的保持。实测数据表明

与单通道超分辨成像算法相比

MCJSR-InISAR算法成像结果的熵值降低了约0.17

且运算复杂度降低了O(10

)。

Abstract

A novel three-dimensional(3-D)imaging algorithm of interferometric inverse synthetic aperture radar(InISAR)using multichannel joint sparse recovery(MCJSR)

named MCJSR-InISAR

is proposed to improve the problem that the super-resolution images recovered by the single channel super-resolution imaging algorithm do not necessarily share the same positions of the scattering centers. The combined range alignment approach is used to correct the envelope delay caused by the target's translational motion

and then the combined phase adjustment approach is employed to complete the phase compensation of translational motion. The range differences between two echo signals received by different antennas are then compensa

ted. Then

MCJSR is used for super-resolution imaging

and the computational efficiency of the proposed algorithm is improved by using the fast Fourier transform(FFT). Finally

a 3-D InISAR imagery of the maneuvering target is obtained by using both the horizontal and the pitching interferometric phase information. The MCJSR-InISAR algorithm can improve the recovery precision of the strong centers in the target scattering field

and preserve effectively the relative phase information between different channels. Experimental results on real-measured data and comparisons with the single channel super-resolution imaging algorithm show that the proposed algorithm decreases the entropy of the resulting image by about 0.17

and reduces the computational complexity by about O(10

关键词

Keywords

references

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