Multistatic MIMO Sparse Imaging Based on FFT and Low-Rank Matrix Recovery Techniques-Reference-Cited by-同舟云学术

Multistatic MIMO Sparse Imaging Based on FFT and Low-Rank Matrix Recovery Techniques

Published:2023-03 Issue:3 Volume:71 Page:1285-1295
ISSN:0018-9480
Container-title:IEEE Transactions on Microwave Theory and Techniques
language:
Short-container-title:IEEE Trans. Microwave Theory Techn.

Author:

Hu Shaoqing¹^ORCID,Molaei Amir Masoud²^ORCID,Yurduseven Okan²^ORCID,Meng Hongying¹^ORCID,Nilavalan Rajagopal¹,Gan Lu¹^ORCID,Chen Xiaodong³^ORCID

Affiliation:

1. Department of Electronic and Electrical Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, U.K.

2. Institute of Electronics, Communications and Information Technology, Queen’s University Belfast, Belfast, U.K.

3. School of Electronic Science and Computer Science, Queen Mary University of London, London, U.K.

Funder

Brunel University London through the 2021 Research Development Fund

Brunel Research Initiative and Enterprise Fund (BRIEF) Award

Leverhulme Trust through the Research Leadership Award

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation

Link

http://xplorestaging.ieee.org/ielx7/22/10061518/09934797.pdf?arnumber=9934797

Reference42 articles.

1. 340-GHz 3-D Imaging Radar With 4Tx-16Rx MIMO Array

2. SAR Imaging With Undersampled Data via Matrix Completion

3. Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

4. Robust principal component analysis?

5. A Novel Fully Electronic Active Real-Time Imager Based on a Planar Multistatic Sparse Array

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