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International Conference on Microwave and Millimeter Wave technology Proceedings

作者： Jinlong Bao Deshuang Zhao Weiping Cao Bing Li Bing-Zhong Wang Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin Institute of Applied Physics University of Electronic Science and Technology of China Chengdu School of Electrical Engineering Southwest JiaoTong University Chengdu

Radiative focusing wireless power transfer (RFWPT) has attracted an increasing attention due to its potential of powering multi-users wirelessly without power cables at a long distance. However, it is still challenging to realize efficient equalized power transfer among users. In this paper, we present an efficient power equalization scheme for multi-user RFWPT system. First, we build a multi-user RFWPT model based on the time reversal focusing theory. Second, we derive the efficiency formula and the conditions for efficient multi-user wireless power transfer, and then present a receiving power equalization scheme for multi-users with the deduced efficiency formula. Finally, we numerically verify the power equalization scheme by full-wave electromagnetic simulations.

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A New Approach for Optimization Selection of Spaceborne SAR Beam Position Parameters

A New Approach for Optimization Selection of Spaceborne SAR ...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Mingang Du Guang-Cai Sun Yandong Cao Mengdao Xing Liang Guo Jun Yang National Laboratory of Radar Signal Processing Xidian University Xi'an China School of Physics and Optoelectronic Engineering Xidian University Xi'an China College of Geomatics Xi'an University of Science and Technology Xi'an China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

In this paper, a new optimized selection method of beam position parameters for spaceborne synthetic aperture radar(SAR) is proposed. Aiming at the difficulty in selecting pulse repeatition frequency (PRF) and observation band width in spaceborne SAR beam position design, this paper deduces the iterative relationship between adjacent beam positions in detail from the spaceborne SAR beam geometry, and proposes an automatic optimization and selection method for beam position parameters. The proposed method meets the principles of PRF restriction and maximum observation band width. The PRF and observation band width of one beam position can be optimized and selected at the same time, and the next beam position parameters can be automatically iteratively selected according to the current selection result. Simulation results validate the effectiveness of the proposed method.

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Optimal Multimodel Representation by Laguerre Filters Applied to a Communicating Two Tank System

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Journal of Systems science & Complexity 2018年第3期31卷 621-646页

作者： SAMEH Adaily ABDELKADER Mbarek TAREK Garna JOSE Ragot Laboratory of Automatic Control Signal and Image Processing National Engineering School of Monastir University of Monastir 5019 Tunisia Higher Institute of Applied Science and Technology of Sousse University of Sousse 4003 Tunisia Center of Research on Automatic of Nancy CNRS 2 Avenue de la for de Haye 54516 Vandoeuvre Cedex France.

This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ARX-Laguerre multimodel, is characterized by the parameter number reduction with a recursive representation. However, a significant reduction of this multimodel is subject to an optimal choice of Laguerre poles characterizing each local linear model ARX-Laguerre. Therefore, the authors propose an optimization algorithm to estimate, from input/output measurements, the optimal values of Laguerre poles. The ARX-Laguerre multimodel as well as the proposed optimization algorithm are tested on a continuous stirred tank reactor system （CSTR）. Moreover, the authors take into account a practical validation on an experimental communicating two tank system （CTTS）.

关键词： ARX-Laguerre model Laguerre poles multimodel approach optimization

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SAR Image Fusion Based on Mathematical Frame 6

SAR Image Fusion Based on Mathematical Frame

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Liu, Yang Liao, Guisheng Li, Shidong Nie, Guoli Zeng, Cao Du, Peiju National Laboratory of Radar Signal Processing XiDian University Xi'an China San Francisco State University San Francisco United States Intl. Coop. Base of Integrated Electronic Information System of Ministry of Science and Technology XiDian University Xi'an China Imaging and Target Recognition Overseas Expertises Introduction Center for Discipline Innovation XiDian University Radar Cognitive Detection Xi'an China

ISBN: (纸本)9781728129129

In this paper, we proposed a frame-based approach to synthetic aperture radar (SAR) images fusion. Specifically, the method consists two parts: image fusion preprocessing and fusion reconstruction. Firstly, we fuse a set of low-resolution (LR) SAR images to form an aligned coarse SAR image which still has image blur caused by the point spread function (PSF) by fusion preprocessing. Then Frame fundamental iterative regularization is used to reconstruct high-resolution (HR) SAR image. Both simulated and real SAR images are used to verify the validity of the method. The results show that details and definition of the LR image processed with the method are effectively improved. © 2019 IEEE.

关键词： Synthetic aperture radar

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Learning compact target-oriented feature representations for visual tracking

arXiv

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arXiv 2019年

作者： Li, Chenglong Huang, Yan Wang, Liang Tang, Jin Lin, Liang Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Institute of Physical Science and Information Technology Anhui University Center for Research on Intelligent Perception and Computing NLPR CASIA School of Data and Computer Science Sun Yat-Sen University

Many state-of-the-art trackers usually resort to the pre-trained convolutional neural network (CNN) model for correlation filtering, in which deep features could usually be redundant, noisy and less discriminative for some certain instances, and the tracking performance might thus be affected. To handle this problem, we propose a novel approach, which takes both advantages of good generalization of generative models and excellent discrimination of discriminative models, for visual tracking. In particular, we learn compact, discriminative and target-oriented feature representations using the Laplacian coding algorithm that exploits the dependence among the input local features in a discriminative correlation filter framework. The feature representations and the correlation filter are jointly learnt to enhance to each other via a fast solver which only has very slight computational burden on the tracking speed. Extensive experiments on three benchmark datasets demonstrate that this proposed framework clearly outperforms baseline trackers with a modest impact on the frame rate, and performs comparably against the state-of-the-art methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Target tracking

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On Error Performance and Concatenated Coding of Polar Codes in AWGN Channels

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IOP Conference Series: Materials science and Engineering 2020年第7期768卷

作者： Jing Jin Rui Deng Tiansheng Liu Liping Li Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) Anhui University Hefei China Department of Electronic Engineering and Information Science University of Science and Technology Hefei China

In additive white Gaussian noise (AWGN) channels, construction of polar codes is needed for every operating signal-to-noise ratio (SNR). Recently, the proposal of the design-SNR reduces the computation effort in constructing polar codes. In this paper, we prove that although the BER performance of the design-SNR construction is not affected, the packet-error-rate (PER) performance is degraded compared with the point-by-point construction. Therefore, a concatenation scheme is proposed to improve the degraded PER performance. Results show the validity of the proposed concatenation scheme when employing the design-SNR construction.

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NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results

arXiv

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arXiv 2020年

作者： Lugmayr, Andreas Danelljan, Martin Timofte, Radu Ahn, Namhyuk Bai, Dongwoon Cai, Jie Cao, Yun Chen, Junyang Cheng, Kaihua Chun, SeYoung Deng, Wei El-Khamy, Mostafa Man Ho, Chiu Ji, Xiaozhong Kheradmand, Amin Kim, Gwantae Ko, Hanseok Lee, Kanghyu Lee, Jungwon Li, Hao Liu, Ziluan Liu, Zhi-Song Liu, Shuai Lu, Yunhua Meng, Zibo Navarrete Michelini, Pablo Micheloni, Christian Prajapati, Kalpesh Ren, Haoyu Hyeok Seo, Yong Siu, Wan-Chi Sohn, Kyung-Ah Tai, Ying Muhammad Umer, Rao Wang, Shuangquan Wang, Huibing Haoning Wu, Timothy Wu, Haoning Yang, Biao Yang, Fuzhi Yoo, Jaejun Zhao, Tongtong Zhou, Yuanbo Zhuo, Haijie Zong, Ziyao Zou, Xueyi Wang, Li-Wen Cani, Marie-Paule Siu, Wan-Chi Yang, Huan Fu, Jianlong Shi, Yukai Chen, Junyang Lee, Kanghyu Park, Jaihyun Lee, Junyeop Min, Jeongki Lee, Bokyeung Ko, Hanseok Yoo, Jaejun Sohn, Kyung-Ah Micheloni, Christian Hu, Fengshuo Wang, Yanhong Lu, Yunhua Peng, Jinjia Wang, Huibing Zhuo, Haijie Lee, Junyeop Min, Jeongki Lee, Bokyeung Park, Jaihyun Ko, Hanseok Tai, Lab Ying Jilin Li, Youtu Lab Liu, Shuai Yang, Biao Liu, Xing Chen, Shuaijun Zhao, Lei Wang, Zhan Lin, Yuxuan Jia, Xu Gao, Qinquan Deng, Wei Kheradmand, Amin El-Khamy, Mostafa Wang, Shuangquan Bai, Dongwoon Lee, Jungwon Patel, Heena Chudasama, Vishal Upla, Kishor Ramachandra, Raghavendra Raja, Kiran Busch, Christoph Meng, Zibo Ho, Chiu Man Computer Vision Lab ETH Zurich Switzerland LIX - Computer science laboratory at the cole polytechnique Palaiseau France Center of Multimedia Signal Processing Hong Kong Polytechnic University Hong Kong Shanghai Jiao Tong University China Microsoft Research Beijing China Guangdong University of Technology China Intelligent Signal Processing Laboratory Korea University Korea Republic of Ajou University Korea Republic of EPFL University of Udine Italy BOE Technology Group Co. Ltd Dalian Maritime University China Guangdong OPPO Mobile Telecommunications Corp. Ltd Department of Video Information Processing Korea University Korea Republic of School of Electrical Engineering Korea University Korea Republic of Tencent Youtu Lab Yun Cao Tencent Youtu Tencent Youtu Lab Chengjie Wang Tencent Tencent Youtu Lab Feiyue Huang Tencent Youtu Lab Peking University China North China University of Technology China Huawei Technologies Co. Ltd China Fuzhou University Tong Tong Fuzhou University Imperial Vision Technology China Fuzhou University Imperial Vision Technology China Imperial Vision Technology SOC R&D Samsung Semiconductor Inc. United States Ulsan national institute of science and technology Korea Republic of Sardar Vallabhbhai National Institute Of Technology Surat India Norwegian University of Science and Technology Gjøvik Norway InnoPeak Technology

This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are unavailable. For training, only one set of source input images is therefore provided along with a set of unpaired high-quality target images. In Track 1: Image processing artifacts, the aim is to super-resolve images with synthetically generated image processing artifacts. This allows for quantitative benchmarking of the approaches w.r.t. a ground-truth image. In Track 2: Smartphone Images, real low-quality smart phone images have to be super-resolved. In both tracks, the ultimate goal is to achieve the best perceptual quality, evaluated using a human study. This is the second challenge on the subject, following AIM 2019, targeting to advance the state-of-the-art in super-resolution. To measure the performance we use the benchmark protocol from AIM 2019. In total 22 teams competed in the final testing phase, demonstrating new and innovative solutions to the problem. Copyright © 2020, The Authors. All rights reserved.

关键词： Optical resolving power

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Kalman Filter Based Equalization for Underwater Acoustic Communications

Kalman Filter Based Equalization for Underwater Acoustic Com...

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OCEANS - Europe

作者： Jun Tao Yanbo Wu Qisong Wu Xiao Han State Key Lab. of Acoustics Chinese Academy of Sciences Beijing China Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education Southeast University Nanjing China Acoustic Science and Technology Laboratory Harbin Engineering University Harbin China

For single-carrier underwater acoustic (UWA) communications, a time-domain channel estimation based equalizer (CEE) is usually overlooked in favor of a direct adaptive equalizer (DAE), mainly due to its high complexity despite potentially better performance. The complexity burden of a CEE is mainly caused by the calculation of the equalizer coefficients, which involves matrix inversion operations at a complexity cubic in the channel length L. The value of L for a UWA channel can amount to several tens or even hundreds, making the CEE scheme prohibitively costly. In this work, a CEE scheme with a complexity quadratic in L is proposed. It is designed from the Kalman filter (KF) perspective and referred as the Kalman equalizer (KE). In the KE, an adaptive channel estimator is coupled with a KF based symbol estimator. The estimated channel is used to construct the KF measurement matrix, and there is no need to compute any equalizer coefficients. Moreover, the channel sparsity can be conveniently utilized to reduce the equalization complexity. The proposed KE scheme was verified by experimental data collected in at-sea trials and showed significant performance gain over a DAE.

关键词： Channel estimation Complexity theory Kalman filters Estimation Phase locked loops Decision feedback equalizers

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A Method of Fast Extract signal Subspace Based on the Householder Transformation

A Method of Fast Extract Signal Subspace Based on the Househ...

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2018 International Computers, signals and Systems Conference, ICOMSSC 2018

作者： Chang, Yu Wan, Qun Xia, Changxiong Wan, Yihe University of Electronic Science and Technology of China School of Electronic Engineering Chengdu China Key Lab of Blind Signal Processing Chengdu China Special Wireless Communication Tongfang Electronic Techology Co. Ltd Jiangxi Province Engineering Research Center Jiujiang China

ISBN: (纸本)9781538667514

The technologies of array signal processing based on subspace decomposition can break the Rayleigh limit, and have great performance and angular resolution. However, in order to obtain signal subspace, traditional methods need to apply singular value decomposition on the signal covariance matrix. Because of the large amount of calculation of singular value decomposition, it is difficult to satisfy the requirements in real-time. Given that the signal covariance matrix is conjugate-symmetric, this paper proposes a new method that can fast compute signal subspace depending on repeatedly applying householder transformation to reduce the covariance matrix order based on the power method, and it has fewer iterations and less amount of calculation. © 2018 IEEE.

关键词： Covariance matrix

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Fractal-scaling non-parametric processing of spatial-temporal flow of real polarimetric information in the radio systems

Fractal-scaling non-parametric processing of spatial-tempora...

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2019 International Conference on Intelligent Computing, Automation and Systems, ICICAS 2019

作者： Potapov, Alexander A. Liu, Weiping German, Vitaliy A. Feng, Tianhua Rekhviashvili, Sergo Sh. V.A. kotel'Nikov Institute of Radio Engineering and Electronics Russian Academy of Sciences Moscow Russia JNU-IREE RAS Joint Laboratory of Information Techniques and Fractal Signal Processing Jinan University Guangzhou China Department of Electronic Engineering College of Information Science and Technology Jinan University Guangzhou China Department of Theoretical and Mathematical Physics Institute of Applied Mathematics and Automation KBSC RAS Nalchik Russia

ISBN: (数字)9781728161068

ISBN: (纸本)9781728161068

关键词： Fractals

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