Results 41 to 50 of about 6,407 (152)

A fast and accurate basis pursuit denoising algorithm with application to super-resolving tomographic SAR [PDF]

, 2018
$L_1$ regularization is used for finding sparse solutions to an underdetermined linear system. As sparse signals are widely expected in remote sensing, this type of regularization scheme and its extensions have been widely employed in many remote sensing
Bamler, Richard, Shi, Yilei, Yin, Wotao, Zhu, Xiao Xiang   +3 more
core   +3 more sources

Near-Field MIMO-SAR Millimeter-Wave Imaging With Sparsely Sampled Aperture Data

IEEE Access, 2019
The primary challenge of a cost-effective and low-complexity near-field millimeter-wave (mmWave) imaging system is to achieve high resolution with a few antenna elements as possible.
Muhammet Emin Yanik, Murat Torlak
doaj   +1 more source

Joint sparsity-driven inversion and model error correction for radar imaging [PDF]

, 2009
Solution of inverse problems in imaging requires the use of a mathematical model of the observation process. However such models often involve errors and uncertainties themselves. The application of interest in this paper is synthetic aperture radar (SAR)
Cetin, Mujdat, Onhon, Ozben Naime, Çetin, Müjdat, Önhon, Özben Naime   +3 more
core   +2 more sources

Improved L1/2 Threshold Iterative High Resolution SAR Imaging Algorithm

Leida xuebao, 2023
An improved Synthetic Aperture Radar (SAR) imaging algorithm is proposed to address the issues of low azimuth resolution and noise interference in the sparse sampling condition.
Zhiqi GAO, Shuchen SUN, Pingping HUANG, Yaolong QI, Wei XU   +4 more
doaj   +1 more source

Parameter selection in sparsity-driven SAR imaging [PDF]

, 2009
We consider a recently developed sparsity-driven synthetic aperture radar (SAR) imaging approach which can produce superresolution, feature-enhanced images.
Batu, Ozge, Batu, Özge, Cetin, Mujdat, Çetin, Müjdat   +3 more
core   +2 more sources

An innovative semantically guided SAR imaging and target enhancement method

Electronics Letters
Conventional sparse synthetic aperture radar (SAR) imaging methods apply regularisation to constrain scene priors. However, these methods often neglect specific target regions, resulting in undifferentiated imaging. This letter introduces a novel network
Guoru Zhou, Zhe Zhang, Bingchen Zhang, Yirong Wu   +3 more
doaj   +1 more source

Ship Wake Detection in SAR Images via Sparse Regularization [PDF]

, 2019
In order to analyse synthetic aperture radar (SAR) images of the sea surface, ship wake detection is essential for extracting information on the wake generating vessels.
Achim, Alin, Karakuş, Oktay, Rizaev, Igor   +2 more
core   +4 more sources

Nonsparse SAR Scene Imaging Network Based on Sparse Representation and Approximate Observations

Remote Sensing, 2023
Sparse-representation-based synthetic aperture radar (SAR) imaging technology has shown superior potential in the reconstruction of nonsparse scenes.
Hongwei Zhang, Jiacheng Ni, Kaiming Li, Ying Luo, Qun Zhang   +4 more
doaj   +1 more source

Experimental Synthetic Aperture Radar with Dynamic Metasurfaces

, 2017
We investigate the use of a dynamic metasurface as the transmitting antenna for a synthetic aperture radar (SAR) imaging system. The dynamic metasurface consists of a one-dimensional microstrip waveguide with complementary electric resonator (cELC ...
Boyarsky, Michael, Fromenteze, Thomas, Imani, Mohammadreza F., Pulido-Mancera, Laura, Reynolds, Matthew, Sleasman, Timothy, Smith, David R.   +6 more
core   +2 more sources

DeepRED Based Sparse SAR Imaging

Remote Sensing
The integration of deep neural networks into sparse synthetic aperture radar (SAR) imaging is explored to enhance SAR imaging performance and reduce the system’s sampling rate. However, the scarcity of training samples and mismatches between the training
Yao Zhao, Qingsong Liu, He Tian, Bingo Wing-Kuen Ling, Zhe Zhang   +4 more
doaj   +1 more source