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SAR Imaging via Efficient Implementations of Sparse ML Approaches

Glentis, George-Othan; Zhao, Kexin; Jakobsson, Andreas LU ; Abeida, Habti and Li, Jian (2014) In Signal Processing 95(February). p.15-26
Abstract
High-resolution spectral estimation techniques are of notable interest for synthetic aperture radar (SAR) imaging. Several sparse estimation techniques have been shown to provide significant performance gains as compared to conventional approaches. We consider efficient implementation of the recent iterative sparse maximum likelihood-based approaches (SMLAs). Furthermore, we present approximative fast SMLA formulation using the Quasi-Newton approach, as well as consider hybrid SMLA-MAP algorithms. The effectiveness of the discussed techniques is illustrated using numerical and experimental examples.
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Synthetic aperture radar imaging, Non-parametric high resolution spectral analysis, Sparse estimators, Efficient algorithms
in
Signal Processing
volume
95
issue
February
pages
15 - 26
publisher
Elsevier
external identifiers
  • wos:000326912000003
  • scopus:84883665118
ISSN
0165-1684
DOI
10.1016/j.sigpro.2013.08.003
language
English
LU publication?
yes
id
2b226bca-03a7-4fce-87d6-f39f00db784b (old id 3993904)
date added to LUP
2013-11-18 13:53:55
date last changed
2017-10-01 03:16:09
@article{2b226bca-03a7-4fce-87d6-f39f00db784b,
  abstract     = {High-resolution spectral estimation techniques are of notable interest for synthetic aperture radar (SAR) imaging. Several sparse estimation techniques have been shown to provide significant performance gains as compared to conventional approaches. We consider efficient implementation of the recent iterative sparse maximum likelihood-based approaches (SMLAs). Furthermore, we present approximative fast SMLA formulation using the Quasi-Newton approach, as well as consider hybrid SMLA-MAP algorithms. The effectiveness of the discussed techniques is illustrated using numerical and experimental examples.},
  author       = {Glentis, George-Othan and Zhao, Kexin and Jakobsson, Andreas and Abeida, Habti and Li, Jian},
  issn         = {0165-1684},
  keyword      = {Synthetic aperture radar imaging,Non-parametric high resolution spectral analysis,Sparse estimators,Efficient algorithms},
  language     = {eng},
  number       = {February},
  pages        = {15--26},
  publisher    = {Elsevier},
  series       = {Signal Processing},
  title        = {SAR Imaging via Efficient Implementations of Sparse ML Approaches},
  url          = {http://dx.doi.org/10.1016/j.sigpro.2013.08.003},
  volume       = {95},
  year         = {2014},
}