Joint Matrix Form SAR Imaging and Autofocus Based on Compressed Sensing

BU Hong-xia; BAI Xia; ZHAO Juan; QI Yao-hui; YAN Ruo-ying

doi:10.3969/j.issn.0372-2112.2017.04.016

您当前的位置：

首页 >

文章列表页 >

Joint Matrix Form SAR Imaging and Autofocus Based on Compressed Sensing

更新时间：2025-07-16

- Joint Matrix Form SAR Imaging and Autofocus Based on Compressed Sensing
- Acta Electronica Sinica Vol. 45, Issue 4, Pages: 874-881(2017)
- 作者机构：
  
  1. 河北师范大学物理科学与信息工程学院,河北,石家庄,050024
  2. 北京理工大学信息与电子学院,北京,100081
  3. 河北师范大学物理科学与信息工程学院,河北,石家庄,050024
  4. 北京理工大学信息与电子学院,北京,100081
- 作者简介：
- 基金信息：
  
  Natural Science Key Program of Colleges and Universities in Hebei Province (No.ZD2016031);Natural Science Research Fund of Hebei Normal University (No.L2016B06, No.L2010Y01)
- DOI：10.3969/j.issn.0372-2112.2017.04.016
  CLC： TN958
- Published Online：25 April 2017，
  
  Published：2017
- 稿件说明：
移动端阅览
BU Hong-xia, BAI Xia, ZHAO Juan, et al. Joint Matrix Form SAR Imaging and Autofocus Based on Compressed Sensing[J]. Acta Electronica Sinica, 2017, 45(4): 874-881.
DOI：

BU Hong-xia, BAI Xia, ZHAO Juan, et al. Joint Matrix Form SAR Imaging and Autofocus Based on Compressed Sensing[J]. Acta Electronica Sinica, 2017, 45(4): 874-881. DOI： 10.3969/j.issn.0372-2112.2017.04.016.

摘要

模型准确情况下，压缩感知在合成孔径雷达成像中得到良好应用；但在实际情况中，模型会存在一定误差，这些误差造成图像偏离真实位置、引起散焦降低成像质量.本文提出一种矩阵型联合CS-SAR成像与自聚焦算法，该算法在CS-SAR成像重构方法方面，基于光滑

范数方法提出了矩阵型正则化光滑

范数重构方法，该方法具有较强容错能力并能直接重构矩阵型信号，能克服现有联合CS-SAR成像与自聚焦算法在计算效率方面的缺陷.最后，通过仿真验证了所提算法的有效性.

Abstract

Compressed sensing (CS) has been successfully applied to the synthetic aperture radar (SAR) imaging.These CS-based SAR imaging algorithms generally assume that the model of the imaging system is accurate.However

in practice it is common to encounter model errors which usually introduce unknown phase errors into the acquired data.The phase errors may cause range migration or defocusing.In this paper

an approach for matrix form joint CS-SAR imaging and autofocus is proposed.Based on smoothed

norm (SL0) algorithm

we develop a matrix form regularized SL0 (MRSL0) algorithm to efficiently perform CS-SAR imaging.The MRSL0 adopts inequality constrain to tolerate phase errors and has fast computation speed due to its matrix form.Exp

eriment results demonstrate that the proposed approach can efficiently reconstruct high quality images using limited amount of measurements.

关键词

Keywords

references

Views

387

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Refocusing for Three-Dimensional Rotating Ship Targets in SAR Images Based on Minimum Entropy Criteria and Generative Adversarial Network

Active Jamming Suppression for SAR Images Based on Self-Supervised Complex-Valued Deep Learning

SAR Recognition Method of Ship Targets for SAR Based on M3Net

Performance Analysis of Scattering Mechanism Identification of Dual-Polarization SAR using a Modified H-α Decomposition

Related Author

XU Dan

JIANG Yi-cheng

REN Hang

ZHANG Yun

HUA Qing-long

JIANG Yi-cheng

JI Zhen-yuan

ZHANG Qian

Related Institution

School of Electronics and Information Engineering， Harbin Institute of Technology

School of Electronics and Information Engineering, Harbin Institute of Technology

Air Force Radar Academy

National University of Defense Technology

Shanghai Jiaotong University

⁰