Results 11 to 20 of about 50 (50)
Aspect-Aided Dynamic Non-Negative Sparse Representation-Based Microwave Image Classification [PDF]
Sensors, 2016 Classification of target microwave images is an important application in much areas such as security, surveillance, etc. With respect to the task of microwave image classification, a recognition algorithm based on aspect-aided dynamic non-negative least square (ADNNLS) sparse representation is proposed.
Xinzheng Zhang 0002 +5 more
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Microwave Imaging From Sparse Measurements for Near-Field Synthetic Aperture Radar
IEEE Transactions on Instrumentation and Measurement, 2017 This paper reports the experimental studies for four image reconstruction methods from sparse measurement using wideband microwave synthetic aperture radar systems. The four methods include two denoising methods using zero filling (ZF) and nonuniform fast Fourier transform (NUFFT), and two compressed sensing (CS) methods using the orthogonal matching ...
Xiahan Yang +3 more
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MICROWAVE IMAGING OF NON-RIGID MOVING TARGET USING 2D SPARSE MIMO ARRAY
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018 This paper develops a microwave/mmw (millimeter-wave) imaging method for moving objects of non-rigid body which can be used in the heavy traffic scenarios. This method is proposed with a 2D sparse MIMO (multiple-input multiple-output) array composed of two orthogonal linear arrays.
Zhanyu Zhu, Lei Kuang, Feng Xu 0001
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Fast Localization of Impact Damage on Woven CFRP Based on Sparse Microwave Imaging [PDF]
, 2020 Microwave open-ended waveguide scanning has been proved to be a promising NDT technique for imaging of woven carbon fiber reinforced plastic (CFRP) with impact damages. However, it uses a conventional C-scan technique, which is excessively time-consuming and therefore it is not practical for defect detection in a large area.
Sutthaweekul, Ruslee, Tian, Gui Yun
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Study on the Sparse Sub-block Microwave Imaging Based on Lasso(In English)
Journal of Radars, 2013 Sparse microwave imaging requires nonlinear algorithm that is expensive for large scene imaging. Therefore, the sub-block imaging method is studied, in which the measured data and the relative imaging region is divided into sub-blocks, and then sparse microwave imaging algorithm based on Least absolute shrinkage and selection operator (Lasso) is ...
Xiang Yin, Zhang Bing-chen, Hong Wen
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Experiment based on orbit satellite and application for sparse microwave imaging
Tongxin xuebao, 2017 The experiment aiming to verify the sparse microwave image methodology based on orbit SAR satellite was presented.During the experiment,the imaging parameters were changed in order to achieve the uniform de-sampling echo data.The image quality evaluation method for sparse microwave imaging was proposed and quantified evaluation results for the ...
Jing TIAN +4 more
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Feature Understanding and Target Detection for Sparse Microwave Synthetic Aperture Radar Images
Leida xuebao, 2016 Sparse microwave imaging using sparse priors of observed scenes in space, time, frequency, or polarization domain and echo data with sampling rate smaller than the traditional Nyquist rate as well as optimization algorithms for reconstructing the microwave images of observed scenes has many advantages over traditional microwave imaging systems.
Zhang Zenghui, Yu Wenxian
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Application of Optimized Sparse Antenna Array in Near Range 3D Microwave Imaging
IEICE Transactions on Communications, 2013 QI, Yaolong +4 more
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On the Use of Spherical Harmonics in Sparse Microwave Imaging
2020 14th European Conference on Antennas and Propagation (EuCAP), 2020In this paper, we introduce a novel microwave imaging method using spherical harmonics and the sparse processing. As the sources of the spherical harmonics, we use the multipoles of different order. Based on theoretical considerations and as shown by numerical examples this approach is capable of retrieving concave shapes, which is particularly ...
Vojnovic Nebojsa +2 more
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Sparse microwave imaging: Principles and applications
Science China Information Sciences, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bingchen Zhang, Wen Hong, Yirong Wu
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