Synthetic Aperture Radar (SAR) Techniques and Applications
Because of its ability to sense the Earth's surface at night and during the day, under any weather condition, Synthetic Aperture Radar (SAR) has become a well-established and powerful remote sensing technology that is used worldwide for numerous applications. This book compiles 19 research work...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2020
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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100 | 1 | |a Bovenga, Fabio |4 edt | |
700 | 1 | |a Bovenga, Fabio |4 oth | |
245 | 1 | 0 | |a Synthetic Aperture Radar (SAR) Techniques and Applications |
260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2020 | ||
300 | |a 1 electronic resource (342 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a Because of its ability to sense the Earth's surface at night and during the day, under any weather condition, Synthetic Aperture Radar (SAR) has become a well-established and powerful remote sensing technology that is used worldwide for numerous applications. This book compiles 19 research works that investigate different aspects of SAR processing, SAR image analysis, and SAR applications. The contributions cover topics related to multi-angle/wide-angle SAR imaging; Doppler parameter estimation; data-driven focusing; Inverse SAR (ISAR) applied to pulsar signal modeling and detection; ground-based SAR; near-field interferometric ISAR; the interaction between SAR signals and the Infosphere; SAR interferometry for ground displacement monitoring, feature extraction, and change detection; and SAR-based sea applications. The selected studies represent real examples of the abundant research ongoing in the field of SAR processing and applications, and they further demonstrate that SAR imaging still presents considerable opportunities for future investigation. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Research & information: general |2 bicssc | |
653 | |a joint sparse reconstruction | ||
653 | |a interferometric inverse synthetic aperture radar | ||
653 | |a compressed sensing | ||
653 | |a near-field 3-D imaging | ||
653 | |a wide angle | ||
653 | |a synthetic aperture radar (SAR) | ||
653 | |a convolutional neural networks (CNNs) | ||
653 | |a deep learning (DL) | ||
653 | |a ship classification | ||
653 | |a Doppler parameter estimation and compensation (DPEC) | ||
653 | |a extended multiple aperture mapdrift (EMAM) | ||
653 | |a very-high-squint airborne SAR imaging | ||
653 | |a spatial variance | ||
653 | |a the derivative of the Doppler rate | ||
653 | |a GB-SAR | ||
653 | |a MIMO radar | ||
653 | |a radar imaging | ||
653 | |a CSAR | ||
653 | |a anisotropy | ||
653 | |a aspect entropy | ||
653 | |a discrimination | ||
653 | |a wide angle SAR | ||
653 | |a LS-CS-Residual | ||
653 | |a aspect dependent | ||
653 | |a polarimetric synthetic aperture radar | ||
653 | |a total electron content | ||
653 | |a ionospheric electron density distribution | ||
653 | |a land subsidence | ||
653 | |a Radarsat-2 images | ||
653 | |a small baseline subset (SBAS) method | ||
653 | |a interferometric synthetic aperture radar (InSAR) | ||
653 | |a inverse synthetic aperture radar (ISAR) | ||
653 | |a moving ship | ||
653 | |a refocusing | ||
653 | |a fast minimum entropy | ||
653 | |a oceanic eddies | ||
653 | |a shear-wave-generated eddies | ||
653 | |a burgers-Rott vortex model | ||
653 | |a SAR image simulation | ||
653 | |a SAR system | ||
653 | |a efficient focusing of SAR data | ||
653 | |a inverse problem | ||
653 | |a remote sensing | ||
653 | |a SAR data-focusing | ||
653 | |a synthetic aperture radar | ||
653 | |a Singular Value Decomposition | ||
653 | |a blind deconvolution | ||
653 | |a signal processing | ||
653 | |a parameter estimation | ||
653 | |a computational modeling | ||
653 | |a SAR imaging | ||
653 | |a multi-angle SAR | ||
653 | |a improved RMA | ||
653 | |a SAR image fusion | ||
653 | |a wide-area surveillance | ||
653 | |a super-resolution | ||
653 | |a Doppler beam sharpening | ||
653 | |a ionosphere | ||
653 | |a P-band | ||
653 | |a reverse back-projection (ReBP) | ||
653 | |a sliding spotlight | ||
653 | |a scintillation | ||
653 | |a SAR | ||
653 | |a 2CMV | ||
653 | |a change detection | ||
653 | |a optical flow | ||
653 | |a k-means | ||
653 | |a K-SVD | ||
653 | |a multi-pass squinted (MPS) | ||
653 | |a azimuth sidelobes suppression | ||
653 | |a ground-based synthetic aperture radar (GBSAR) | ||
653 | |a arc-scanning synthetic aperture radar (ArcSAR) | ||
653 | |a interferometric ArcSAR | ||
653 | |a DEM assisted SAR imaging | ||
653 | |a deformation model | ||
653 | |a time series deformation | ||
653 | |a rheological parameter | ||
653 | |a highway | ||
653 | |a passive ISAR asteroid imaging | ||
653 | |a pulsar emission signal modeling | ||
653 | |a multi-angle/wide angle SAR | ||
653 | |a inverse SAR | ||
653 | |a ground-based SAR | ||
653 | |a ionospheric effects | ||
653 | |a SAR interferometry | ||
653 | |a SAR image analysis | ||
653 | |a SAR image change detection | ||
653 | |a SAR sea applications | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/2358 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/68596 |7 0 |z DOAB: description of the publication |