Article
Engineering, Electrical & Electronic
Yifan Wang, Ziyu Hua, Jiachen Shi, Zongren Dai, Jiagang Wang, Liyang Shao, Yidong Tan
Summary: We propose and demonstrate a novel LiDAR system for 3-D imaging, combining LFI and FMCW. The system effectively enhances the amplitude of the generated beat signal, improving the sensitivity in weak-signal detection with low photon consumption. The system inherits the advantages of FMCW, measuring position and velocity simultaneously. Experimental results show valid distance and velocity measurement, and the system achieves high-quality 3-D imaging over 65 m away with a portable prototype.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Clinical Neurology
Vanessa Wiggermann, Verena Endmayr, Enedino Hernandez-Torres, Romana Hoeftberger, Gregor Kasprian, Simon Hametner, Alexander Rauscher
Summary: Magnetic resonance imaging (MRI) can provide important insights into multiple sclerosis (MS) by detecting focal or diffuse myelin damage or remyelination. This study used three myelin-sensitive MRI scans and histopathological measurements to evaluate the different stages of MS pathology, including chronic demyelinated and remyelinated lesions. The results showed that inactive lesions in chronic MS cases had increased myelin densities, indicating low-level remyelination.
Article
Engineering, Electrical & Electronic
Chuan Ye, Yunhan Li, Chao Wang, Yuanyao Hu
Summary: A deep learning line laser 3-D measurement method based on feature fusion and attention mechanism is proposed to address the impact of reflected workpieces. A UNet segmentation model is established to solve the interference caused by reflection and segment the overall distribution and bending characteristics of laser stripes. The Steger algorithm is used to extract the center of the laser stripe, and the contour polygon segmentation method is used to obtain the segmentation points of the laser stripe. Polynomial fitting is then performed to obtain a smoother laser stripe centerline. The proposed method effectively overcomes interference and generates a smoother 3-D model.
IEEE SENSORS JOURNAL
(2023)
Article
Geochemistry & Geophysics
Mou Wang, Shunjun Wei, Jun Shi, Xiaoling Zhang, Yongxin Guo
Summary: In this paper, a new perceptual learning framework named PeFIST-Net is proposed for 3-D synthetic aperture radar (SAR) imaging. The proposed method improves reconstruction accuracy by unfolding the fast iterative shrinkage-thresholding algorithm (FISTA) and exploring the sparse prior offered by convolutional neural network (CNN). Experimental results demonstrate that the proposed method can obtain well-focused SAR images from highly incomplete echoes while maintaining fast computational speed.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Mou Wang, Shunjun Wei, Zichen Zhou, Jun Shi, Xiaoling Zhang, Yongxin Guo
Summary: In this research, a new network structure LLRS-Net is proposed to obtain improved reconstructions from sparsely sampled 3-D SAR echoes by utilizing learned low-rank and sparse priors. The effectiveness of this method is validated in both theoretical and experimental settings through a two-stage reconstruction algorithmic framework LSRA and the cascaded network structure LLRS-Net.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Automation & Control Systems
Weihao Zhang, Jiapeng Wang, Min Tang, Honglin Ma, Linzhi Wang, Qi Zhang, Shuqian Fan
Summary: Defects in metal 3-D printing process are difficult to predict and control, hindering its application in critical industrial fields. This study utilizes a machine vision monitoring system to monitor the forming process, and designs a 2-D transformer-based framework for video classification to recognize unhealthy melt tracks.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Ling Pu, Xiaoling Zhang, Jun Shi, Shunjun Wei, Tianwen Zhang, Xu Zhan
Summary: This article proposes a method for precise RCS extrapolation via NF 3-D imaging with adaptive parameter optimization Bayesian learning, improving precision, stability, and image quality of NF 3-D imaging, as well as ensuring high accuracy of RCS extrapolation.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2022)
Article
Geochemistry & Geophysics
Tong Gu, Guisheng Liao, Yachao Li, Yongjun Liu, Yifan Guo
Summary: This study proposes a novel hyperparameter-free gridless-based sparse reconstruction algorithm by combining the optimal covariance fitting criterion and atomic norm. Extensive numerical simulations were conducted to demonstrate the advantages and effectiveness of this algorithm for DLSLA 3D SAR imaging.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Computer Science, Information Systems
Handan Jing, Shiyong Li, Ke Miao, Shuoguang Wang, Xiaoxi Cui, Guoqiang Zhao, Houjun Sun
Summary: This paper proposes a complex-valued fully convolutional neural network (CVFCNN) based method to address the issues of high computational complexity and unstable image quality in the compressive sensing (CS) method. By designing the CVFCNN structure and deriving the formulas of the complex-valued back-propagation algorithm, a new activation function is introduced to improve the performance of CVFCNN. Compared to the real-valued fully convolutional neural network (RVFCNN), the proposed CVFCNN achieves better performance while requiring fewer parameters.
Article
Engineering, Electrical & Electronic
Ling Pu, Xiaoling Zhang, Jun Shi, Bokun Tian, Shunjun Wei
Summary: The study introduces an improved Sparse Bayesian (SB) 3-D imaging algorithm using dyadic Green's function, which effectively resolves low-RCS objects and achieves better imaging accuracy than existing algorithms.
IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Handan Jing, Shiyong Li, Xiaoxi Cui, Guoqiang Zhao, Houjun Sun
Summary: A method for multifocus image fusion based on the criterion of minimum entropy is proposed in this letter, which can be further utilized for any kind of the MMW imaging system working at a single frequency. Simulations and experiments verify the effectiveness of the proposed method.
IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS
(2021)
Article
Materials Science, Multidisciplinary
Tsukasa Terada, Reona Kitaura, Shintaro Ishigaki, Takafumi Ishibe, Nobuyasu Naruse, Yutaka Mera, Ryoji Asahi, Yoshiaki Nakamura
Summary: Seed-assisted epitaxy (SAE) is a technique that enables the epitaxial growth of intermetallic materials on Si substrates. In SAE, amorphous films of the intermetallic compound are deposited on nanoseeds, and epitaxial growth is achieved through annealing. The interface between the nanoseeds and the films facilitates the epitaxial growth, and the composition ratio controls the orientation of the grown structure.
Editorial Material
Engineering, Aerospace
James Park, Raghu G. Raj, Marco Martorella, Elisa Giusti
Summary: This article introduces a method for polarimetric 3-D ISAR imaging using multiple phase centers and a multilook algorithm, which improves target classification and identification, as well as enhances accuracy of height estimation in noisy conditions.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Yijiang Nan, Xiaojing Huang, Y. Jay Guo
Summary: This article proposes a low-cost 3-D millimeter-wave holographic imaging system using helical scanning with multiple receivers. It addresses the computational cost issue and introduces a novel 3-D helical imaging algorithm.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2022)
Article
Geochemistry & Geophysics
Jianqiu Wang, Kang Liu, Hongyan Liu, Kaicheng Cao, Yongqiang Cheng, Hongqiang Wang
Summary: This article presents a solution to achieve 3-D electromagnetic (EM) vortex imaging in radar imaging technology by effectively utilizing the relative motion between radar and target in the line-of-sight direction, resulting in superior imaging performance.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)