Compressed Sensing Radar Imaging With Compensation of Observation Position Error

被引:43
作者
Yang, Jungang [1 ]
Huang, Xiaotao [1 ]
Thompson, John [2 ]
Jin, Tian [1 ]
Zhou, Zhimin [1 ]
机构
[1] Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China
[2] Univ Edinburgh, Joint Res Inst Signal & Image Proc, Inst Digital Commun, Edinburgh EH9 3JL, Midlothian, Scotland
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2014年 / 52卷 / 08期
基金
中国国家自然科学基金;
关键词
Autofocus; compressed sensing (CS); observation position error; radar imaging; SPARSE REPRESENTATION; SIGNAL RECOVERY; AIRBORNE SAR; AUTOFOCUS;
D O I
10.1109/TGRS.2013.2283054
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Compressed sensing (CS) based radar imaging requires the use of a mathematical model of the observation process. Inaccuracies in the observation model may cause defocusing in the reconstructed images. In the observation process, the observation positions are usually not known perfectly. Imperfect knowledge of the observation positions is a major source of model errors in imaging. In this paper, a method is proposed to compensate the observation position errors in CS-based radar imaging. Instead of treating the observation-position-induced model errors as phase errors in the data, the proposed method can determine the observation position errors as part of the imaging process. It uses an iterative algorithm, which cycles through steps of target reconstruction and observation position error estimation and compensation. The proposed method can estimate the observation position errors accurately, and the reconstruction quality of the target images can be improved significantly. Simulation results and experimental results from rail-mounted radar and airborne synthetic aperture radar are presented to show the effectiveness of the proposed method.
引用
收藏
页码:4608 / 4620
页数:13
相关论文
共 47 条
[1]  
Abolghasemi V., 2012, P COSERA BONN GERM M
[2]  
[Anonymous], 2005, P IEEE INT RAD C
[3]  
[Anonymous], 2015, Linear and Nonlinear Programming
[4]  
Baraniuk Richard, 2007, 2007 IEEE Radar Conference, P128, DOI 10.1109/RADAR.2007.374203
[5]   IEEE-SPS and connexions - An open access education collaboration [J].
Baraniuk, Richard G. ;
Burrus, C. Sidney ;
Thierstein, E. Joel .
IEEE SIGNAL PROCESSING MAGAZINE, 2007, 24 (06) :6-+
[6]   Three-Dimensional SAR Focusing From Multipass Signals Using Compressive Sampling [J].
Budillon, Alessandra ;
Evangelista, Annarita ;
Schirinzi, Gilda .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2011, 49 (01) :488-499
[7]  
Candès EJ, 2008, IEEE SIGNAL PROC MAG, V25, P21, DOI 10.1109/MSP.2007.914731
[8]   Near-optimal signal recovery from random projections: Universal encoding strategies? [J].
Candes, Emmanuel J. ;
Tao, Terence .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2006, 52 (12) :5406-5425
[9]   Stable signal recovery from incomplete and inaccurate measurements [J].
Candes, Emmanuel J. ;
Romberg, Justin K. ;
Tao, Terence .
COMMUNICATIONS ON PURE AND APPLIED MATHEMATICS, 2006, 59 (08) :1207-1223
[10]   Feature-preserving regularization method for complex-valued inverse problems with application to coherent imaging [J].
Çetin, M ;
Karl, WC ;
Willsky, AS .
OPTICAL ENGINEERING, 2006, 45 (01)