Superresolution ISAR Imaging Based on Sparse Bayesian Learning
- Author
- HONGCHAO LIU1 ; BO JIU1 ; HONGWEI LIU1 ; ZHENG BAO1
[1] National Key Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China - Source
IEEE transactions on geoscience and remote sensing. 2014, Vol 52, Num 8, pp 5005-5013, 9 p ; 2 ; ref : 26 ref
- CODEN
- IGRSD2
- ISSN
- 0196-2892
- Scientific domain
- Agronomy, agriculture, phytopathology; Ecology; Geology; Geophysics; Telecommunications
- Publisher
- Institute of Electrical and Electronics Engineers, New York, NY
- Publication country
- United States
- Document type
- Article
- Language
- English
- Author keyword
- Compressive sensing (CS) inverse synthetic aperture radar (SAR) (ISAR) sparse Bayesian learning (SBL)
- Keyword (fr)
- Algorithme Bilan Classification Coût Dégradation Performance Radar ouverture synthétique Régression Très haute résolution Télédétection Apprentissage ISAR
- Keyword (en)
- algorithms balance classification cost degradation performances Synthetic aperture radar regression very high resolution remote sensing
- Keyword (es)
- Algoritmo Balance Clasificación Costo Regresión Detección a distancia
- Classification
- Pascal
- 001 Exact sciences and technology / 001E Earth, ocean, space / 001E01 Earth sciences / 001E01M Internal geophysics / 001E01M04 Applied geophysics
- Discipline
- Earth sciences
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 28721427
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Access to the document
Install on your browser
DOI
10.1109/TGRS.2013.2286402 
https://dx.doi.org/10.1109/TGRS.2013.2286402
"O:13:\"PanistOpenUrl\":36:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000idc\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1109\/TGRS.2013.2286402\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:62:\"Superresolution ISAR Imaging Based on Sparse Bayesian Learning\";s:9:\"\u0000*\u0000jtitle\";s:50:\"IEEE transactions on geoscience and remote sensing\";s:9:\"\u0000*\u0000stitle\";s:31:\"IEEE trans. geosci. remote sens\";s:7:\"\u0000*\u0000date\";s:4:\"2014\";s:9:\"\u0000*\u0000volume\";s:2:\"52\";s:8:\"\u0000*\u0000issue\";s:1:\"8\";s:8:\"\u0000*\u0000spage\";s:4:\"5005\";s:8:\"\u0000*\u0000epage\";s:4:\"5013\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0196-2892\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"HONGCHAO LIU\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:3:{i:0;s:6:\"BO JIU\";i:1;s:11:\"HONGWEI LIU\";i:2;s:9:\"ZHENG BAO\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"IGRSD2\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:1:\"2\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:62:\"Superresolution ISAR Imaging Based on Sparse Bayesian Learning\";s:8:\"\u0000*\u0000place\";s:12:\"New York, NY\";s:6:\"\u0000*\u0000pub\";s:49:\"Institute of Electrical and Electronics Engineers\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"9\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Panist access
"O:12:\"IstexOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1109\/TGRS.2013.2286402\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:62:\"Superresolution ISAR Imaging Based on Sparse Bayesian Learning\";s:9:\"\u0000*\u0000jtitle\";s:50:\"IEEE transactions on geoscience and remote sensing\";s:9:\"\u0000*\u0000stitle\";s:31:\"IEEE trans. geosci. remote sens\";s:7:\"\u0000*\u0000date\";s:4:\"2014\";s:9:\"\u0000*\u0000volume\";s:2:\"52\";s:8:\"\u0000*\u0000issue\";s:1:\"8\";s:8:\"\u0000*\u0000spage\";s:4:\"5005\";s:8:\"\u0000*\u0000epage\";s:4:\"5013\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0196-2892\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"HONGCHAO LIU\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:3:{i:0;s:6:\"BO JIU\";i:1;s:11:\"HONGWEI LIU\";i:2;s:9:\"ZHENG BAO\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"IGRSD2\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:1:\"2\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:62:\"Superresolution ISAR Imaging Based on Sparse Bayesian Learning\";s:8:\"\u0000*\u0000place\";s:12:\"New York, NY\";s:6:\"\u0000*\u0000pub\";s:49:\"Institute of Electrical and Electronics Engineers\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"9\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Istex access
"O:16:\"UnpaywallOpenUrl\":35:{s:8:\"\u0000*\u0000email\";s:27:\"assistance-portail@inist.fr\";s:6:\"\u0000*\u0000fmt\";N;s:6:\"\u0000*\u0000doi\";s:25:\"10.1109\/TGRS.2013.2286402\";s:6:\"\u0000*\u0000pii\";N;s:7:\"\u0000*\u0000pmid\";N;s:9:\"\u0000*\u0000atitle\";N;s:9:\"\u0000*\u0000jtitle\";N;s:9:\"\u0000*\u0000stitle\";N;s:7:\"\u0000*\u0000date\";N;s:9:\"\u0000*\u0000volume\";N;s:8:\"\u0000*\u0000issue\";N;s:8:\"\u0000*\u0000spage\";N;s:8:\"\u0000*\u0000epage\";N;s:8:\"\u0000*\u0000pages\";N;s:7:\"\u0000*\u0000issn\";N;s:8:\"\u0000*\u0000eissn\";N;s:9:\"\u0000*\u0000aulast\";N;s:10:\"\u0000*\u0000aufirst\";N;s:9:\"\u0000*\u0000auinit\";N;s:10:\"\u0000*\u0000auinitm\";N;s:5:\"\u0000*\u0000au\";N;s:9:\"\u0000*\u0000aucorp\";N;s:7:\"\u0000*\u0000isbn\";N;s:8:\"\u0000*\u0000coden\";N;s:8:\"\u0000*\u0000genre\";N;s:7:\"\u0000*\u0000part\";N;s:9:\"\u0000*\u0000btitle\";N;s:8:\"\u0000*\u0000title\";N;s:8:\"\u0000*\u0000place\";N;s:6:\"\u0000*\u0000pub\";N;s:10:\"\u0000*\u0000edition\";N;s:9:\"\u0000*\u0000tpages\";N;s:9:\"\u0000*\u0000series\";N;s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";N;}"
Unpaywall access
"O:16:\"EuropePMCOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1109\/TGRS.2013.2286402\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:62:\"Superresolution ISAR Imaging Based on Sparse Bayesian Learning\";s:9:\"\u0000*\u0000jtitle\";s:50:\"IEEE transactions on geoscience and remote sensing\";s:9:\"\u0000*\u0000stitle\";s:31:\"IEEE trans. geosci. remote sens\";s:7:\"\u0000*\u0000date\";s:4:\"2014\";s:9:\"\u0000*\u0000volume\";s:2:\"52\";s:8:\"\u0000*\u0000issue\";s:1:\"8\";s:8:\"\u0000*\u0000spage\";s:4:\"5005\";s:8:\"\u0000*\u0000epage\";s:4:\"5013\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0196-2892\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"HONGCHAO LIU\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:3:{i:0;s:6:\"BO JIU\";i:1;s:11:\"HONGWEI LIU\";i:2;s:9:\"ZHENG BAO\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"IGRSD2\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:1:\"2\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:62:\"Superresolution ISAR Imaging Based on Sparse Bayesian Learning\";s:8:\"\u0000*\u0000place\";s:12:\"New York, NY\";s:6:\"\u0000*\u0000pub\";s:49:\"Institute of Electrical and Electronics Engineers\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"9\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Europe PubMed Central access
"O:12:\"ArXivOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1109\/TGRS.2013.2286402\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:62:\"Superresolution ISAR Imaging Based on Sparse Bayesian Learning\";s:9:\"\u0000*\u0000jtitle\";s:50:\"IEEE transactions on geoscience and remote sensing\";s:9:\"\u0000*\u0000stitle\";s:31:\"IEEE trans. geosci. remote sens\";s:7:\"\u0000*\u0000date\";s:4:\"2014\";s:9:\"\u0000*\u0000volume\";s:2:\"52\";s:8:\"\u0000*\u0000issue\";s:1:\"8\";s:8:\"\u0000*\u0000spage\";s:4:\"5005\";s:8:\"\u0000*\u0000epage\";s:4:\"5013\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0196-2892\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"HONGCHAO LIU\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:3:{i:0;s:6:\"BO JIU\";i:1;s:11:\"HONGWEI LIU\";i:2;s:9:\"ZHENG BAO\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"IGRSD2\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:1:\"2\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:62:\"Superresolution ISAR Imaging Based on Sparse Bayesian Learning\";s:8:\"\u0000*\u0000place\";s:12:\"New York, NY\";s:6:\"\u0000*\u0000pub\";s:49:\"Institute of Electrical and Electronics Engineers\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"9\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
arXiv access
