NDLI: 2D single snapshot imaging using MIMO radar based on SR

Content Provider	IET Digital Library
Author	Chen, Chunhui Zhang, Qun Gu, Fufei Luo, Ying
Abstract	To overcome the disadvantages of the required motion compensation in the traditional inverse synthetic aperture radar imaging of moving targets, a 2D single snapshot imaging method using a MIMO radar based on the sparse representation (SR) is proposed. It can simultaneously recover a real-time 2D image and avoid motion compensation. By exploiting the sparsity and data structure of the echo signals, a 2D SR model is established. The SR problem is solved based on the compressed sensing theory and the 2D smoothed L0 algorithm. Finally, the 2D image of the target can be reconstructed at low signal-to-noise ratio and high compressed ratio, which is advantageous for target recognition and classification. Compared with the existing 1D methods, the proposed method can directly recover 2D images and has lower computational complexity. Simulations are performed to verify the effectiveness of the method.
Starting Page	1946
Ending Page	1948
Page Count	3
ISSN	00135194
Volume Number	52
e-ISSN	1350911X
Issue Number	Issue 23, Nov (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/52/23
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2016.3076
Journal	Electronics Letters
Publisher	The Institution of Engineering and Technology
Publisher Date	2016-10-18
Access Restriction	Open
Rights License	Creative Commons Attribution-Non Commercial-No Derivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
Subject Keyword	1D Method 2D Image Recovery 2D Single Snapshot Imaging Method 2D Smoothed L0 Algorithm 2D SR Model Compressed Sensing Compressed Sensing Theory Computational Complexity Data Structure Echo Signal High Compressed Ratio Image Classification Image Recognition Image Reconstruction Image Representation Inverse Synthetic Aperture Radar Imaging Low Signal-to-noise Ratio MIMO Radar Motion Compensation Radar Equipment Radar Imaging Radar Target Recognition Sparse Representation System And Application Target Classification Target Recognition
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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