The Race to Improve Radar Imagery: An overview of recent progress in statistical sparsity-based techniques

The Race to Improve Radar Imagery: An overview of recent progress in statistical sparsity-based techniques

The exploitation of sparsity has significantly advanced the field of radar imaging over the last few decades, leading to substantial improvements in the resolution and quality of the processed images. More recent developments in compressed sensing (CS) suggest that statistical sparsity can lead to f...

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Bibliographic Details
Main Authors: Zhao, Lifan, Wang, Lu, Yang, Lei, Zoubir, Abdelhak M., Bi, Guoan
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2016
Subjects:
Statistical analysis
Image quality
Online Access:https://hdl.handle.net/10356/84674
http://hdl.handle.net/10220/41933
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Institution: Nanyang Technological University
Language: English
Description
Summary:The exploitation of sparsity has significantly advanced the field of radar imaging over the last few decades, leading to substantial improvements in the resolution and quality of the processed images. More recent developments in compressed sensing (CS) suggest that statistical sparsity can lead to further performance benefits by imposing sparsity as a statistical prior on the considered signal. In this article, a comprehensive survey is made of recent progress on statistical sparsity based techniques for various radar imagery applications.

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