Results 11 to 20 of about 9,039 (172)
Parametric Sparse Representation and Its Applications to Radar Sensing
Leida xuebao, 2016 Sparse signal processing has been utilized to the area of radar sensing. Due to the presence of unknown factors such as the motion of the targets of interest and the error of the radar trajectory, a predesigned dictionary cannot provide the optimally ...
Li Gang, Xia Xiang-Gen
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Low-rank sparse matrix decomposition for sparsity-driven SAR image reconstruction [PDF]
, 2015 We consider the development of a synthetic aperture radar (SAR) image reconstruction method that decomposes the imaged field into a sparse and a low-rank component.
Soğanlı, Abdurrahim, Çetin, Müjdat
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Near-Field 3D Sparse SAR Direct Imaging with Irregular Samples
Remote Sensing, 2022 Sparse imaging is widely used in synthetic aperture radar (SAR) imaging. Compared with the traditional matched filtering (MF) methods, sparse SAR imaging can directly image the scattered points of a target and effectively reduce the sidelobes and clutter
Shiqi Xing +5 more
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Sparsity-driven image formation and space-variant focusing for SAR [PDF]
, 2011 In synthetic aperture radar (SAR) imaging, the presence of moving targets in the scene causes phase errors in the SAR data and subsequently defocusing in the formed image. The defocusing caused by the moving targets exhibits space-variant characteristics,
Çetin, Müjdat, Önhon, Özben Naime
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Four-dimensional SAR Imaging Algorithm Based on Iterative Reconstruction of Magnitude and Phase
Leida xuebao, 2016 Observation data obtained from the Four-Dimensional (4D) Synthetic Aperture Radar (SAR) system is sparse and non-uniform in the baseline-time plane. Hence, the imaging results acquired by traditional Fourier-based methods are limited by high side lobes ...
Ren Xiaozhen, Yang Ruliang
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Multiple feature-enhanced synthetic aperture radar imaging [PDF]
, 2009 Non-quadratic regularization based image formation is a recently proposed framework for feature-enhanced radar imaging. Specific image formation techniques in this framework have so far focused on enhancing one type of feature, such as strong point ...
Cetin, Mujdat +3 more
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Remote Sensing, 2015 Normally, polarimetric SAR classification is a high-dimensional nonlinear mapping problem. In the realm of pattern recognition, sparse representation is a very efficacious and powerful approach.
Fan Yang, Wei Gao, Bin Xu, Jian Yang
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Sparse signal representation for complex-valued imaging [PDF]
, 2009 We propose a sparse signal representation-based method for complex-valued imaging. Many coherent imaging systems such as synthetic aperture radar (SAR) have an inherent random phase, complex-valued nature.
Cetin, Mujdat +3 more
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SAR moving target imaging in a sparsity-driven framework [PDF]
, 2011 In synthetic aperture radar (SAR) imaging, sparsity-driven imaging techniques have been shown to provide high resolution images with reduced sidelobes and reduced speckle, by allowing the incorporation of prior information about the scene into the ...
Cetin, Mujdat +3 more
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A sparsity-driven approach for joint SAR imaging and phase error correction [PDF]
, 2012 Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the observation model may cause various degradations and artifacts in the reconstructed ...
Çetin, Müjdat, Önhon, Özben Naime
core +5 more sources