Deep Unfolding of Iteratively Reweighted ADMM for Wireless RF Sensing

Deep Unfolding of Iteratively Reweighted ADMM for Wireless RF Sensing

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We address the detection of material defects, which are inside a layered material structure using compressive sensing-based multiple-input and multiple-output (MIMO) wireless radar. Here, strong clutter due to the reflection of the layered structure’s surface often makes the detection of the defects...

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Bibliographic Details
Main Authors: Jung, P. (Author), Miriya Thanthrige, U.S.K.P (Author), Sezgin, A. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
algorithm unfolding
Algorithm unfolding
Clutter (information theory)
clutter suppression
Clutter suppression
Compressed sensing
compressive sensing
Compressive sensing
Deep learning
Defect detection
Defects
defects detection
Detection of materials
Echo suppression
Iterative methods
Layered Structures
Material defect
Mean square error
MIMO systems
Radar clutter
reweighted norm
Reweighted norm
Speed of convergence
Unfoldings
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