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SAR Imaging via Eff...
SAR Imaging via Efficient Implementations of Sparse ML Approaches
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Glentis, George-Othan (författare)
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Zhao, Kexin (författare)
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- Jakobsson, Andreas (författare)
- Lund University,Lunds universitet,Biomedical Modelling and Computation,Forskargrupper vid Lunds universitet,Statistical Signal Processing Group,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Lund University Research Groups,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
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Abeida, Habti (författare)
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Li, Jian (författare)
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(creator_code:org_t)
- Elsevier BV, 2014
- 2014
- Engelska.
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 95:February, s. 15-26
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http://dx.doi.org/10...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Synthetic aperture radar imaging
- Non-parametric high resolution spectral analysis
- Sparse estimators
- Efficient algorithms
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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