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Book
Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics
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ISBN: 3039214101 3039214098 9783039214105 Year: 2019 Publisher: Basel, Switzerland : MDPI,

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Abstract

The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The articles contained in this compilation were presented at the EUROMECH Colloquium 597, « Reduced Order Modeling in Mechanics of Materials », held in Bad Herrenalb, Germany, from August 28th to August 31th 2018. In this book, Artificial Neural Networks are coupled to physics-based models. The tensor format of simulation data is exploited in surrogate models or for data pruning. Various reduced order models are proposed via machine learning strategies applied to simulation data. Since reduced order models have specific approximation errors, error estimators are also proposed in this book. The proposed numerical examples are very close to engineering problems. The reader would find this book to be a useful reference in identifying progress in machine learning and reduced order modeling for computational mechanics.

Keywords

supervised machine learning --- proper orthogonal decomposition (POD) --- PGD compression --- stabilization --- nonlinear reduced order model --- gappy POD --- symplectic model order reduction --- neural network --- snapshot proper orthogonal decomposition --- 3D reconstruction --- microstructure property linkage --- nonlinear material behaviour --- proper orthogonal decomposition --- reduced basis --- ECSW --- geometric nonlinearity --- POD --- model order reduction --- elasto-viscoplasticity --- sampling --- surrogate modeling --- model reduction --- enhanced POD --- archive --- modal analysis --- low-rank approximation --- computational homogenization --- artificial neural networks --- unsupervised machine learning --- large strain --- reduced-order model --- proper generalised decomposition (PGD) --- a priori enrichment --- elastoviscoplastic behavior --- error indicator --- computational homogenisation --- empirical cubature method --- nonlinear structural mechanics --- reduced integration domain --- model order reduction (MOR) --- structure preservation of symplecticity --- heterogeneous data --- reduced order modeling (ROM) --- parameter-dependent model --- data science --- Hencky strain --- dynamic extrapolation --- tensor-train decomposition --- hyper-reduction --- empirical cubature --- randomised SVD --- machine learning --- inverse problem plasticity --- proper symplectic decomposition (PSD) --- finite deformation --- Hamiltonian system --- DEIM --- GNAT


Book
Learning to Understand Remote Sensing Images: Volume 2
Author:
ISBN: 3038976997 3038976989 9783038976998 Year: 2019 Publisher: Basel, Switzerland : MDPI,

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Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

metadata --- image classification --- sensitivity analysis --- ROI detection --- residual learning --- image alignment --- adaptive convolutional kernels --- Hough transform --- class imbalance --- land surface temperature --- inundation mapping --- multiscale representation --- object-based --- convolutional neural networks --- scene classification --- morphological profiles --- hyperedge weight estimation --- hyperparameter sparse representation --- semantic segmentation --- vehicle classification --- flood --- Landsat imagery --- target detection --- multi-sensor --- building damage detection --- optimized kernel minimum noise fraction (OKMNF) --- sea-land segmentation --- nonlinear classification --- land use --- SAR imagery --- anti-noise transfer network --- sub-pixel change detection --- Radon transform --- segmentation --- remote sensing image retrieval --- TensorFlow --- convolutional neural network --- particle swarm optimization --- optical sensors --- machine learning --- mixed pixel --- optical remotely sensed images --- object-based image analysis --- very high resolution images --- single stream optimization --- ship detection --- ice concentration --- online learning --- manifold ranking --- dictionary learning --- urban surface water extraction --- saliency detection --- spatial attraction model (SAM) --- quality assessment --- Fuzzy-GA decision making system --- land cover change --- multi-view canonical correlation analysis ensemble --- land cover --- semantic labeling --- sparse representation --- dimensionality expansion --- speckle filters --- hyperspectral imagery --- fully convolutional network --- infrared image --- Siamese neural network --- Random Forests (RF) --- feature matching --- color matching --- geostationary satellite remote sensing image --- change feature analysis --- road detection --- deep learning --- aerial images --- image segmentation --- aerial image --- multi-sensor image matching --- HJ-1A/B CCD --- endmember extraction --- high resolution --- multi-scale clustering --- heterogeneous domain adaptation --- hard classification --- regional land cover --- hypergraph learning --- automatic cluster number determination --- dilated convolution --- MSER --- semi-supervised learning --- gate --- Synthetic Aperture Radar (SAR) --- downscaling --- conditional random fields --- urban heat island --- hyperspectral image --- remote sensing image correction --- skip connection --- ISPRS --- spatial distribution --- geo-referencing --- Support Vector Machine (SVM) --- very high resolution (VHR) satellite image --- classification --- ensemble learning --- synthetic aperture radar --- conservation --- convolutional neural network (CNN) --- THEOS --- visible light and infrared integrated camera --- vehicle localization --- structured sparsity --- texture analysis --- DSFATN --- CNN --- image registration --- UAV --- unsupervised classification --- SVMs --- SAR image --- fuzzy neural network --- dimensionality reduction --- GeoEye-1 --- feature extraction --- sub-pixel --- energy distribution optimizing --- saliency analysis --- deep convolutional neural networks --- sparse and low-rank graph --- hyperspectral remote sensing --- tensor low-rank approximation --- optimal transport --- SELF --- spatiotemporal context learning --- Modest AdaBoost --- topic modelling --- multi-seasonal --- Segment-Tree Filtering --- locality information --- GF-4 PMS --- image fusion --- wavelet transform --- hashing --- machine learning techniques --- satellite images --- climate change --- road segmentation --- remote sensing --- tensor sparse decomposition --- Convolutional Neural Network (CNN) --- multi-task learning --- deep salient feature --- speckle --- canonical correlation weighted voting --- fully convolutional network (FCN) --- despeckling --- multispectral imagery --- ratio images --- linear spectral unmixing --- hyperspectral image classification --- multispectral images --- high resolution image --- multi-objective --- convolution neural network --- transfer learning --- 1-dimensional (1-D) --- threshold stability --- Landsat --- kernel method --- phase congruency --- subpixel mapping (SPM) --- tensor --- MODIS --- GSHHG database --- compressive sensing


Book
Learning to Understand Remote Sensing Images: Volume 1
Author:
ISBN: 3038976857 3038976849 9783038976851 Year: 2019 Publisher: Basel, Switzerland : MDPI,

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Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

metadata --- image classification --- sensitivity analysis --- ROI detection --- residual learning --- image alignment --- adaptive convolutional kernels --- Hough transform --- class imbalance --- land surface temperature --- inundation mapping --- multiscale representation --- object-based --- convolutional neural networks --- scene classification --- morphological profiles --- hyperedge weight estimation --- hyperparameter sparse representation --- semantic segmentation --- vehicle classification --- flood --- Landsat imagery --- target detection --- multi-sensor --- building damage detection --- optimized kernel minimum noise fraction (OKMNF) --- sea-land segmentation --- nonlinear classification --- land use --- SAR imagery --- anti-noise transfer network --- sub-pixel change detection --- Radon transform --- segmentation --- remote sensing image retrieval --- TensorFlow --- convolutional neural network --- particle swarm optimization --- optical sensors --- machine learning --- mixed pixel --- optical remotely sensed images --- object-based image analysis --- very high resolution images --- single stream optimization --- ship detection --- ice concentration --- online learning --- manifold ranking --- dictionary learning --- urban surface water extraction --- saliency detection --- spatial attraction model (SAM) --- quality assessment --- Fuzzy-GA decision making system --- land cover change --- multi-view canonical correlation analysis ensemble --- land cover --- semantic labeling --- sparse representation --- dimensionality expansion --- speckle filters --- hyperspectral imagery --- fully convolutional network --- infrared image --- Siamese neural network --- Random Forests (RF) --- feature matching --- color matching --- geostationary satellite remote sensing image --- change feature analysis --- road detection --- deep learning --- aerial images --- image segmentation --- aerial image --- multi-sensor image matching --- HJ-1A/B CCD --- endmember extraction --- high resolution --- multi-scale clustering --- heterogeneous domain adaptation --- hard classification --- regional land cover --- hypergraph learning --- automatic cluster number determination --- dilated convolution --- MSER --- semi-supervised learning --- gate --- Synthetic Aperture Radar (SAR) --- downscaling --- conditional random fields --- urban heat island --- hyperspectral image --- remote sensing image correction --- skip connection --- ISPRS --- spatial distribution --- geo-referencing --- Support Vector Machine (SVM) --- very high resolution (VHR) satellite image --- classification --- ensemble learning --- synthetic aperture radar --- conservation --- convolutional neural network (CNN) --- THEOS --- visible light and infrared integrated camera --- vehicle localization --- structured sparsity --- texture analysis --- DSFATN --- CNN --- image registration --- UAV --- unsupervised classification --- SVMs --- SAR image --- fuzzy neural network --- dimensionality reduction --- GeoEye-1 --- feature extraction --- sub-pixel --- energy distribution optimizing --- saliency analysis --- deep convolutional neural networks --- sparse and low-rank graph --- hyperspectral remote sensing --- tensor low-rank approximation --- optimal transport --- SELF --- spatiotemporal context learning --- Modest AdaBoost --- topic modelling --- multi-seasonal --- Segment-Tree Filtering --- locality information --- GF-4 PMS --- image fusion --- wavelet transform --- hashing --- machine learning techniques --- satellite images --- climate change --- road segmentation --- remote sensing --- tensor sparse decomposition --- Convolutional Neural Network (CNN) --- multi-task learning --- deep salient feature --- speckle --- canonical correlation weighted voting --- fully convolutional network (FCN) --- despeckling --- multispectral imagery --- ratio images --- linear spectral unmixing --- hyperspectral image classification --- multispectral images --- high resolution image --- multi-objective --- convolution neural network --- transfer learning --- 1-dimensional (1-D) --- threshold stability --- Landsat --- kernel method --- phase congruency --- subpixel mapping (SPM) --- tensor --- MODIS --- GSHHG database --- compressive sensing


Book
Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement
Authors: ---
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

Radar-related technology is mainly processed within the time and frequency domains but, at the same time, is a multi-dimensional integrated system including a spatial domain for transmitting and receiving electromagnetic waves. As a result of the enormous technological advancements of the pioneers actively discussed in this book, research and development in multi-dimensional undeveloped areas is expected to continue. This book contains state-of-the-art work that should guide your research.

Keywords

History of engineering & technology --- inverse synthetic aperture ladar (ISAL) --- maneuvering target --- integral cubic phase function (ICPF) --- fractional Fourier transform (FRFT) --- non-uniform fast Fourier transform (NUFFT) --- CLEAN technique --- simultaneous polarimetric radar --- constant modulus sequences --- correlation properties --- doppler tolerance --- saliency preprocessing LLC --- saliency detection --- image processing --- scene classification --- antenna array --- automatic guided vehicle --- DoA/DoD estimation --- MIMO radar --- direct position determination --- Doppler --- Doppler rate --- maximum likelihood estimator --- coherent pulse trains --- single moving sensor --- Cramer–Rao lower bound --- bistatic MIMO radar --- DOD/DOA estimation --- mutual coupling --- off-grid sparse problem --- unmanned aerial vehicle --- clustering methods --- man-made targets --- synthetic aperture radar (SAR) --- inverse synthetic aperture radar (ISAR) --- polarimetric decomposition --- Synthetic Aperture Radar (SAR) --- microwave imaging --- constitutive parameters --- conductivity --- permittivity --- tomography --- RF MEMS --- switch --- analytical approach --- low control voltage --- high switching speed --- high reliability --- radar echo cancellation --- frequency shifting modulation --- interrupted sampling --- radar jamming --- deception jamming --- remote sensing --- SAR --- radon transform --- speckle noise filtering --- maritime traffic monitoring --- wake detection and analysis --- synthetic aperture radar --- differential SAR tomography --- squinted SAR --- 3-D deformation --- 2-D PPS --- maneuvering target detection --- coherent integration --- motion parameter estimation --- second-order phase difference (SoPD) --- time-frequency analysis --- image fusion --- sparse representation --- hyperbolic tangent function --- guided filter --- narrowband interference separation --- block sparse Bayesian learning --- sensing matrix optimization --- block coherence measure --- bistatic inverse synthetic aperture radar --- linear geometry distortion --- prior information --- least square error --- lunar penetrating radar --- local correlation --- SNR --- K-L transform --- seislet transform --- generative adversarial nets --- through-wall radar imaging --- multipath ghost suppression --- generator and discriminator --- ultrahigh resolution --- spaceborne --- curved orbit --- series reversion --- singular value decomposition (SVD) --- deramping-based approach --- crosshole ground penetrating radar (GPR) --- Bayesian inversion --- Markov chain Monte Carlo (MCMC) --- forward model --- modeling error --- discrete cosine transform (DCT) --- through-wall imaging --- contrast target detection --- clutter reduction --- entropy thresholding --- low-rank approximation --- S-transformation --- ISAR --- micro-Doppler --- synchrosqueezing --- PBR (passive bistatic radar) --- clutter suppression --- non-uniform grid --- dilation morphology --- passive bistatic radar --- phased array radar --- parameter estimation --- aircraft surveillance --- GPR --- seasonal permafrost --- electromagnetic wave attribute --- relative water content --- marine radar --- wind direction retrieval --- small wind streak --- local gradient method --- adaptive reduced method --- energy spectrum method --- metamaterial absorber --- double negative --- dual-band --- FMCW radio altimeter --- methodological error --- critical height --- altitude measurement accuracy --- height pulses --- ultra-wide frequency deviation --- sparse recovery --- wideband noise interference --- dechirping --- subspace extraction --- denoising detection --- orthogonal matching pursuit --- pulse radar --- rotating target --- micro-motion feature extraction --- interrupted transmitting and receiving (ITR) --- dual-polarized radar --- DOA estimation --- atomic norm --- comprehensive SAR --- multiparametric SAR observation --- discrete scatterer model --- n/a --- Cramer-Rao lower bound


Book
Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement
Authors: ---
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Export citation

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Bookmark

Abstract

Radar-related technology is mainly processed within the time and frequency domains but, at the same time, is a multi-dimensional integrated system including a spatial domain for transmitting and receiving electromagnetic waves. As a result of the enormous technological advancements of the pioneers actively discussed in this book, research and development in multi-dimensional undeveloped areas is expected to continue. This book contains state-of-the-art work that should guide your research.

Keywords

inverse synthetic aperture ladar (ISAL) --- maneuvering target --- integral cubic phase function (ICPF) --- fractional Fourier transform (FRFT) --- non-uniform fast Fourier transform (NUFFT) --- CLEAN technique --- simultaneous polarimetric radar --- constant modulus sequences --- correlation properties --- doppler tolerance --- saliency preprocessing LLC --- saliency detection --- image processing --- scene classification --- antenna array --- automatic guided vehicle --- DoA/DoD estimation --- MIMO radar --- direct position determination --- Doppler --- Doppler rate --- maximum likelihood estimator --- coherent pulse trains --- single moving sensor --- Cramer–Rao lower bound --- bistatic MIMO radar --- DOD/DOA estimation --- mutual coupling --- off-grid sparse problem --- unmanned aerial vehicle --- clustering methods --- man-made targets --- synthetic aperture radar (SAR) --- inverse synthetic aperture radar (ISAR) --- polarimetric decomposition --- Synthetic Aperture Radar (SAR) --- microwave imaging --- constitutive parameters --- conductivity --- permittivity --- tomography --- RF MEMS --- switch --- analytical approach --- low control voltage --- high switching speed --- high reliability --- radar echo cancellation --- frequency shifting modulation --- interrupted sampling --- radar jamming --- deception jamming --- remote sensing --- SAR --- radon transform --- speckle noise filtering --- maritime traffic monitoring --- wake detection and analysis --- synthetic aperture radar --- differential SAR tomography --- squinted SAR --- 3-D deformation --- 2-D PPS --- maneuvering target detection --- coherent integration --- motion parameter estimation --- second-order phase difference (SoPD) --- time-frequency analysis --- image fusion --- sparse representation --- hyperbolic tangent function --- guided filter --- narrowband interference separation --- block sparse Bayesian learning --- sensing matrix optimization --- block coherence measure --- bistatic inverse synthetic aperture radar --- linear geometry distortion --- prior information --- least square error --- lunar penetrating radar --- local correlation --- SNR --- K-L transform --- seislet transform --- generative adversarial nets --- through-wall radar imaging --- multipath ghost suppression --- generator and discriminator --- ultrahigh resolution --- spaceborne --- curved orbit --- series reversion --- singular value decomposition (SVD) --- deramping-based approach --- crosshole ground penetrating radar (GPR) --- Bayesian inversion --- Markov chain Monte Carlo (MCMC) --- forward model --- modeling error --- discrete cosine transform (DCT) --- through-wall imaging --- contrast target detection --- clutter reduction --- entropy thresholding --- low-rank approximation --- S-transformation --- ISAR --- micro-Doppler --- synchrosqueezing --- PBR (passive bistatic radar) --- clutter suppression --- non-uniform grid --- dilation morphology --- passive bistatic radar --- phased array radar --- parameter estimation --- aircraft surveillance --- GPR --- seasonal permafrost --- electromagnetic wave attribute --- relative water content --- marine radar --- wind direction retrieval --- small wind streak --- local gradient method --- adaptive reduced method --- energy spectrum method --- metamaterial absorber --- double negative --- dual-band --- FMCW radio altimeter --- methodological error --- critical height --- altitude measurement accuracy --- height pulses --- ultra-wide frequency deviation --- sparse recovery --- wideband noise interference --- dechirping --- subspace extraction --- denoising detection --- orthogonal matching pursuit --- pulse radar --- rotating target --- micro-motion feature extraction --- interrupted transmitting and receiving (ITR) --- dual-polarized radar --- DOA estimation --- atomic norm --- comprehensive SAR --- multiparametric SAR observation --- discrete scatterer model --- n/a --- Cramer-Rao lower bound


Book
Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement
Authors: ---
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

Radar-related technology is mainly processed within the time and frequency domains but, at the same time, is a multi-dimensional integrated system including a spatial domain for transmitting and receiving electromagnetic waves. As a result of the enormous technological advancements of the pioneers actively discussed in this book, research and development in multi-dimensional undeveloped areas is expected to continue. This book contains state-of-the-art work that should guide your research.

Keywords

History of engineering & technology --- inverse synthetic aperture ladar (ISAL) --- maneuvering target --- integral cubic phase function (ICPF) --- fractional Fourier transform (FRFT) --- non-uniform fast Fourier transform (NUFFT) --- CLEAN technique --- simultaneous polarimetric radar --- constant modulus sequences --- correlation properties --- doppler tolerance --- saliency preprocessing LLC --- saliency detection --- image processing --- scene classification --- antenna array --- automatic guided vehicle --- DoA/DoD estimation --- MIMO radar --- direct position determination --- Doppler --- Doppler rate --- maximum likelihood estimator --- coherent pulse trains --- single moving sensor --- Cramer-Rao lower bound --- bistatic MIMO radar --- DOD/DOA estimation --- mutual coupling --- off-grid sparse problem --- unmanned aerial vehicle --- clustering methods --- man-made targets --- synthetic aperture radar (SAR) --- inverse synthetic aperture radar (ISAR) --- polarimetric decomposition --- Synthetic Aperture Radar (SAR) --- microwave imaging --- constitutive parameters --- conductivity --- permittivity --- tomography --- RF MEMS --- switch --- analytical approach --- low control voltage --- high switching speed --- high reliability --- radar echo cancellation --- frequency shifting modulation --- interrupted sampling --- radar jamming --- deception jamming --- remote sensing --- SAR --- radon transform --- speckle noise filtering --- maritime traffic monitoring --- wake detection and analysis --- synthetic aperture radar --- differential SAR tomography --- squinted SAR --- 3-D deformation --- 2-D PPS --- maneuvering target detection --- coherent integration --- motion parameter estimation --- second-order phase difference (SoPD) --- time-frequency analysis --- image fusion --- sparse representation --- hyperbolic tangent function --- guided filter --- narrowband interference separation --- block sparse Bayesian learning --- sensing matrix optimization --- block coherence measure --- bistatic inverse synthetic aperture radar --- linear geometry distortion --- prior information --- least square error --- lunar penetrating radar --- local correlation --- SNR --- K-L transform --- seislet transform --- generative adversarial nets --- through-wall radar imaging --- multipath ghost suppression --- generator and discriminator --- ultrahigh resolution --- spaceborne --- curved orbit --- series reversion --- singular value decomposition (SVD) --- deramping-based approach --- crosshole ground penetrating radar (GPR) --- Bayesian inversion --- Markov chain Monte Carlo (MCMC) --- forward model --- modeling error --- discrete cosine transform (DCT) --- through-wall imaging --- contrast target detection --- clutter reduction --- entropy thresholding --- low-rank approximation --- S-transformation --- ISAR --- micro-Doppler --- synchrosqueezing --- PBR (passive bistatic radar) --- clutter suppression --- non-uniform grid --- dilation morphology --- passive bistatic radar --- phased array radar --- parameter estimation --- aircraft surveillance --- GPR --- seasonal permafrost --- electromagnetic wave attribute --- relative water content --- marine radar --- wind direction retrieval --- small wind streak --- local gradient method --- adaptive reduced method --- energy spectrum method --- metamaterial absorber --- double negative --- dual-band --- FMCW radio altimeter --- methodological error --- critical height --- altitude measurement accuracy --- height pulses --- ultra-wide frequency deviation --- sparse recovery --- wideband noise interference --- dechirping --- subspace extraction --- denoising detection --- orthogonal matching pursuit --- pulse radar --- rotating target --- micro-motion feature extraction --- interrupted transmitting and receiving (ITR) --- dual-polarized radar --- DOA estimation --- atomic norm --- comprehensive SAR --- multiparametric SAR observation --- discrete scatterer model

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