Parameter-Refined OMP for Compressive Radar Imaging of Rotating Targets

Ngoc Hung Nguyen; Dogancay Kutluyil; Tran Hai-Tan; Berry Paul E.

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Parameter-Refined OMP for Compressive Radar Imaging of Rotating Targets

机译：参数精制OMP用于旋转目标的压缩雷达成像

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This paper presents a new parameter-refined orthogonal matching pursuit method to tackle the dictionary mismatch problem arising in compressive radar imaging of a rotating target with off-grid scatterers. The main idea is to replace the linear least-squares projection step of the conventional orthogonal matching pursuit (OMP) method with a nonlinear least-squares procedure which jointly estimates the off-grid positions and reflectivities of true scatterers. Simulations are presented to corroborate the performance advantages of the proposed method.

机译：本文提出了一种新的参数精炼正交匹配追踪方法，以解决旋转靶的压缩雷达成像中出现的字典不匹配问题，其与离网散射脉冲散。主要思想是用非线性最小二乘过程替换传统正交匹配追踪（OMP）方法的线性最小二乘投影步骤，该非线性最小二乘过程共同估计真实散射体的离网位置和反射率。提出了仿真以证实提出的方法的性能优势。

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来源
《IEEE Transactions on Aerospace and Electronic Systems》 |2019年第6期|3561-3577|共17页
作者
Ngoc Hung Nguyen; Dogancay Kutluyil; Tran Hai-Tan; Berry Paul E.;
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作者单位

Def Sci & Technol Grp Maritime Div Edinburgh SA 5111 Australia|Univ South Australia Sch Engn Mawson Lakes SA 5095 Australia;

Univ South Australia Sch Engn Mawson Lakes SA 5095 Australia;

Def Sci & Technol Grp Natl Secur & ISR Div Edinburgh SA 5111 Australia;

Def Sci & Technol Grp Natl Secur & ISR Div Edinburgh SA 5111 Australia;

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正文语种 eng
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关键词
Compressive radar imaging; micromotion; nonlinear least-squares (NLS); parameter perturbation; sparse reconstruction;

机译：压缩雷达成像;微观;非线性最小二乘（NLS）;参数扰动;稀疏重建;

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专利

1. Compressive Radar Imaging of Stationary Indoor Targets With Low-Rank Plus Jointly Sparse and Total Variation Regularizations [J] . Tang Van Ha, Bouzerdoum Abdesselam, Phung Son Lam IEEE Transactions on Image Processing . 2020,第期

机译：静止室内目标的压缩雷达成像，低级别加上共同稀疏和总变化规范化
2. Narrow-band radar imaging for off-grid spinning targets via compressed sensing [J] . Sun Chao, Wang Baoping, Fang Yang, Multidimensional systems and signal processing . 2017,第4期

机译：窄带雷达成像，通过压缩传感来实现离网旋转靶标
3. Novel compressive sensing-based Dechirp-Keystone algorithm for synthetic aperture radar imaging of moving target [J] . Yang Jiefang, Zhang Yunhua Radar, Sonar & Navigation, IET . 2015,第5期

机译：基于压缩感知的新型Dechirp-Keystone算法用于运动目标合成孔径雷达成像
4. Nonlinear Least-Squares Post-Processing for Compressive Radar Imaging of a Rotating Target [C] . Ngoc Hung Nguyen, Kutluyll Doğancay, Hai-Tan Tran, International Conference on Radar . 2018

机译：旋转目标的压缩雷达成像的非线性最小二乘后处理
5. Compressive imaging for difference image formation and wide-field-of-view target tracking. [D] . Shikhar. 2010

机译：压缩成像，用于差异图像形成和宽视野目标跟踪。
6. Compressive Sensing for Tomographic Imaging of a Target with a Narrowband Bistatic Radar [O] . Ngoc Hung Nguyen, Paul Berry, Hai-Tan Tran 2019

机译：窄带双雷达的目标断层图像压缩感应
7. 1Compressive Sensing Based High-Resolution Polarimetric Through-the-Wall Radar Imaging Exploiting Target Characteristics [O] . Qisong Wu, Yimin D. Zhang, Senior Member, 2015

机译：1基于压缩感知的高分辨率极化穿墙雷达成像开发目标特征

Parameter-Refined OMP for Compressive Radar Imaging of Rotating Targets

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