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Spatial compressive sensing for MIMO radar
Marco Rossi
,
Alexander M. Haimovich
, Yonina C. Eldar
Electrical and Computer Engineering
The Elisha Yegal Bar-Ness Center for Wireless Information Processing
Research output
:
Contribution to journal
›
Article
›
peer-review
247
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Scopus citations
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Keyphrases
Compressed Sensing
100%
Multiple-input-multiple-output Radar
100%
Multiple-input multiple-output Array
50%
Uniform Recovery
50%
Measurement Matrix
50%
Isotropy
50%
High-resolution
25%
Numerical Results
25%
Beamforming
25%
Spatial Domain
25%
Direction of Arrival
25%
Target Localization
25%
Nyquist
25%
Number of Degrees of Freedom
25%
Array Aperture
25%
Sensing Framework
25%
Virtual multiple-input multiple-output (V-MIMO)
25%
Structured Random Matrix
25%
Virtual Array Aperture
25%
Recovery Algorithm
25%
Angle Resolution
25%
Number of Elements
25%
Recovery Guarantee
25%
Sparse Source Localization
25%
Engineering
Compressive Sensing
100%
Multiple-Input Multiple-Output
100%
Measurement Matrix
40%
Isotropy
40%
Degree of Freedom
20%
High Resolution
20%
Beamforming
20%
Spatial Domain
20%
Direction of Arrival
20%
Target Localization
20%
Nyquist Frequency
20%
Classical Method
20%
Physics
MIMO (Control Systems)
100%
Coherence
40%
Isotropy
40%
High Resolution
20%
Degree of Freedom
20%
Direction of Arrival
20%
Beamforming
20%