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3rd International Conference on Advanced Algorithms and signal Image processing, AASIP 2023

作者： Deng, Xin Li, Min Ren, Xiaojun Zheng, Xiuyan Liang, Fei He, Liang Zhu, Min School of Software Xinjiang University China School of Information Science and Engineering Xinjiang University China Xinjiang Key Laboratory of Clinical Genetic Testing and Biomedical Information China Xinjiang Clinical Research Center for Precision Medicine of Digestive System Tumor China Department of Pathology Karamay Central Hospital China Xinjiang Key Laboratory of Signal Detection and Processing China Dept. of Electron. Eng. and Beijing National Research Center for Information Science and Technology Tsinghua University China

ISBN: (纸本)9781510668522

Histopathological images are one of the common diagnostic tools used in the medical field. However, the complex cellular and tissue structures inside colorectal cancer histopathological images make it difficult for physicians to perform efficient cancer diagnosis and quantitative analysis. Therefore, this study proposed a multi-Task learning-based pathology image classification method Multi-TransPathoNet (A transfer learning-based neural network for pathology image classification with multi-Task learning, Multi-TransPathoNet) for detection and visualization output of colorectal cancer histopathology images, thus helping to improve medical efficiency. To verify the practical application value of this method, this study used the paracancerous, highly differentiated, and high-moderately differentiated histopathological images which are more difficult to distinguish in colorectal cancer as the dataset for classification test, and our method obtained 92% accuracy. Besides, we compared with the single-Task learning models Resnet50 and Vgg19 respectively, which also have good performance in image classification tasks, to comprehensively evaluate the proposed model's performance. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Computer aided diagnosis

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An equivalent range model based on time resampling for high-speed maneuvering platform SAR 9

An equivalent range model based on time resampling for high-...

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2019 9th International Workshop on Computer science and Engineering, WCSE 2019

作者： Wang, Anyi Jiao, Xiaoyang Guo, Ping Lin, Chunhui College of Communication and Information Engineering Xi'an University of Science and Technology Xi'an710054 China National Laboratory of Radar Signal Processing Xidian University Xi'an710071 China

ISBN: (纸本)9789811416842

For the high-speed maneuvering platform SAR, the high-speed state will lead to stop-go assumption invalid and the forward acceleration would severely reduce the depth of focusing field in azimuth, thus the traditional range model with stop-go assumption will be ineffective. In this paper, the accurate range history is derived in a geometric configuration for high-speed maneuvering platform SAR and a new range equation is derived by transformation of bistatic to monostatic survey. Based on the new range equation, the azimuth time resampling is proposed by which one can obtain a simplified range equation with a form similar to that of the conventional SAR case. Then the typical imaging methods can be applied directly without any modification. Simulation results verify the effectiveness of the proposed method. © WCSE 2019. All rights reserved.

关键词： Synthetic aperture radar

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Aiding AUV Localization Using a Dual-Sided Synthetic Aperture Sonar

Aiding AUV Localization Using a Dual-Sided Synthetic Apertur...

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2021 CIE International Conference on radar, radar 2021

作者： Chen, Shiping Chi, Cheng Zhang, Pengfei Wang, Peng Li, Yu Liu, Jiyuan Huang, Haining Institute of Acoustics Chinese Academy of Sciences University of Chinese Academy of Sciences Chinese Academy of Sciences Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing Beijing China

ISBN: (纸本)9781665498142

Autonomous underwater vehicle (AUV) navigation and localization is crucial and challenging in Global Positioning System-denied environments. AUV carrying synthetic aperture sonars (SASs) can provide precise motion estimation of the platforms. This study focuses on enhancing the performance of AUV localization using dual-sided SASs. The two-dimensional velocities of AUV are estimated using dual-sided SAS echoes. An extended Kalman filter (EKF) is then adopted for dead reckoning using the estimated velocities. The experimental results demonstrate that the proposed method has better localization accuracy than that of the Doppler velocity log (DVL). © 2021 IEEE.

关键词： autonomous underwater vehicles localization synthetic aperture sonar time delay estimation

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Accurate Elimination Method of 3-D Acceleration for Highly Squinted TOPS SAR with Curved Trajectory 2

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2nd China International SAR Symposium, CISS 2021

作者： Zhang, Gang Liu, Ya Li, Qingqing Liang, Yi Xidian University National Laboratory of Radar Signal Processing Xi'an China First Military Representative Office in Shanghai Air Force Equipment Department Shanghai China Shanghai Academy of Spaceflight Technology Shanghai Radio Equipment Research Institute Shanghai China

ISBN: (纸本)9787000000001

When terrain observation by progressive scans synthetic aperture radar (TOPS SAR) system is mounted on a maneuvering platform, 3-D acceleration introduces envelope error and phase error into the complicated full aperture echo, which makes TOPS SAR image defocused. To solve this problem, a pre-processing is firstly performed to eliminate the spatially invariant envelope error of 3-D acceleration. Subsequently, a wavenumber-domain keystone transform is constructed to equalize the spatially variant linear Doppler phase. Finally, a wavenumber-domain resampling is adopted to equalize the higher-order Doppler phase, including spatial variance of Doppler rate and the azimuth-dependent phase error introduced by 3-D acceleration. Point target simulation shows that the proposed method can handle curved trajectory in highly squinted TOPS SAR geometry. © 2021 SISE.

关键词： Acceleration

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Resource Allocation for Multiple Target Tracking in Active and Passive radar Network

Resource Allocation for Multiple Target Tracking in Active a...

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2021 CIE International Conference on radar, radar 2021

作者： Dai, Jinhui Mo, Xiuci Pu, Wenqiang Yan, Junkun Wang, Penghui Liu, Hongwei Xidian University National Laboratory of Radar Signal Processing Xi'an China Leihua Electronic Technology Research Institution Aviation Industry Corporation of China Wuxi China Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781665498142

A joint beam selection and power allocation (JBSPA) scheme is proposed for multiple target tracking (MTT) in active and passive radar network. The motivation of JBSPA is to exploit not only the degrees of freedom of power for active radars but also the degrees of freedom of receive beams for passive radars, thereby improving the overall tracking accuracy of multiple targets. The predictive Posterior Cramér-Rao lower bound is utilized to evaluate the impact of each allocation strategy on tracking performance, and then the JBSPA scheme is formulated as a mixed integer nonlinear program problem. To solve the formulation efficiently, an alternating direction method of multipliers is developed for an optimum. Numerical results demonstrate that the JBSPA scheme can achieve a significant improvement of the overall MTT accuracy, compared with conventional uniform allocation. © 2021 IEEE.

关键词： multiple target tracking nonconvex optimization radar network resource allocation

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Base Station Selection Method for UWB Indoor Positioning Based on TDOA Fingerprint 5

Base Station Selection Method for UWB Indoor Positioning Bas...

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5th IEEE Information technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Wang, Mei Yang, Fan Zhou, Zou Qiu, Hongbing Guilin University of Electronic Technology Ministry of Education Key Laboratory of Cognitive Radio and Information Processing Guilin541004 China College of Information Science and Engineering Guilin University of Technology Guilin541007 China Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (数字)9781665415996

ISBN: (纸本)9781665415989

The ultrawideband (UWB) indoor positioning system has poor positioning accuracy and stability in the indoor environment with complex structure, which is affected by non-line-of-sigh (NLOS), multi-path effect, physical measurement and other factors. Therefore, this paper proposes a UWB base station (BS) selection positioning method based on time difference of arrival (TDOA) fingerprint. Firstly, TDOA information and BS selection information of the reference point are collected in the off-line phase. Secondly, in the on-line phase, the improved time reversal resonating strength (TRRS) algorithm is used to match the fingerprint database, and the BS selection information recorded by the fingerprint points with the highest matching degree is used for positioning solution. Finally, according to the experimental data, in the 30m*5.5m*3.1m NLOS exhibition hall, the average three-dimensional error is 10.93cm, and the average variance is 10.27cm2. The experimental results show that the proposed method has high reliability and stability. © 2021 IEEE.

关键词： Time difference of arrival

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Effects of colored noise on the dynamics of quantum entanglement of a one-parameter qubit-qutrit system

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Chinese Physics B 2022年第5期31卷 141-149页

作者： Odette Melachio Tiokang Fridolin Nya Tchangnwa Jaures Diffo Tchinda Arthur Tsamouo Tsokeng Martin Tchoffo Research Unit of Condensed Matter Electronic and Signal ProcessingDepartment of PhysicsDschang School of Sciences and TechnologyUniversity of DschangPO Box:67 DschangCameroon Material Science Research Group Physics LaboratoryDepartment of PhysicsPost Graduate SchoolUniversity of MarouaPO Box:814 MarouaCameroon Centre d’Etudes et de Recherches en Agronomie et en Biodiversite Faculte d’Agronomie et des Sciences AgricolesUniversite de DschangCameroun

We analyzed the effect of colored noise on the negativity dynamics of a hybrid system consisting of a qubit-qutrit and not interacting,prepared from the start in an entangled one-parameter state and acting with noise in local and non-local *** this pink and brown noise we investigated two different situations:in the first situation,the noise is produced by a bistable oscillator with an unknown exchange rate;however,in the second situation,the noise is generated by a set of bistable *** found that entanglement decreases with time to zero,and undergoes the phenomenon of sudden death and *** pink noise is more prone to entanglement than the brown noise and the non-local environment is more prone to entanglement than the local *** the number of fluctuators is increased,entanglement decays faster and finally,for certain parameters of the initial state,the subsystems are not affected by the noise.

关键词： entanglement hybrid system qutrit colored noise

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A Multiple Instance Learning Algorithm Using Graph Convolutional Network for Speech Content Classification 5

A Multiple Instance Learning Algorithm Using Graph Convoluti...

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5th IEEE Information technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Zhang, Jianyi Yao, Jiaqi Chu, Yanjie Yan, Jikun PLA Strategic Support Force Information Engineering University College of Information System Engineering Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9781665415989

Recently, speech content classification begins to be formulated as a multiple instance learning (MIL) problem by some researchers. Under the MIL framework, a speech signal is considered as a bag with labels, and speech fragments are regarded as instances without corresponding labels. On this basis, we propose a new algorithm, named MI-CNN-G, for speech content classification using Graph Convolutional Network (GCN) under the MIL framework. First, we only train the MIL classifier, whose architecture is based on Convolutional Neural Network, for bag classification. Second, we utilize GCN to handle graphs composed of instance features that are the outputs of the MIL classifier for correcting the predicted probabilities of the classifier and then updated the classifier and GCN together. Finally, we employ the MI-CNN-G model to predict the labels of unknown bags. The experimental results show that GCN is effective in improving the performance of the MIL classifier on speech content classification and the MI-CNN-G model outperforms the baseline approaches in the Average Precision metric. © 2021 IEEE.

关键词： Convolutional neural networks

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A multi-feature classification approach based on tensor and air distance for inshore ambiguity identification with multichannel SAR system 5

A multi-feature classification approach based on tensor and ...

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IET International radar Conference 2020, IET IRC 2020

作者： Han, Chaolei Yang, Zhiwei Zhang, Qingjun Li, Xianghai He, Pengyuan National Laboratory of Radar Signal Processing Xidian University Xi'an710071 China China Academy of Space Technology Beijing100094 China

ISBN: (纸本)9781839535635

In inshore region, it is crucial to identify azimuth ambiguity for moving target (or ship) detection with multichannel synthetic aperture radar (SAR) system. To this end, a multi-feature classification approach based on tensor and affine invariant Riemannian (AIR) distance is proposed in this paper. The proposed method firstly extracts feature tensor (FT) of multichannel SAR images, including correlation coefficient between channels, multi-look interference phase, and spatial structural gradient information. Then, the core feature tensor (CFT) is obtained by alternating optimization and unfolded along the feature dimension and the feature covariance matrix (FCM) is constructed for each range-Doppler unit (RDU). With the AIR distance measure, the inshore region is divided into different clutter regions. Finally, the experiments on real measured data by TerraSAR-X demonstrate that the proposed method can accurately identify the azimuth ambiguity in inshore region. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Tensors

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Long-Time Coherent Integration and Detection for Asteroid Targets in a Space-based radar System Based on Particle Swarm Optimization

Long-Time Coherent Integration and Detection for Asteroid Ta...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Feng You Penghui Huang Guisheng Liao Donghong Wang Xingzhao Liu Yongyan Sun Guozhong Chen School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China National Laboratory of Radar Signal Processing Xidian University Xi’an China Beijing Institute of Tracking and Telecommunications Technology Beijing China Institute of Shanghai Satellite Engineer Shanghai China

The space-based surveillance radar system has a higher field of view and can overcome interference from Earth's atmosphere and terrain occlusion, which has been widely applied in high-threat near-Earth asteroid (NEA) warning and defense applications. Due to the limited power aperture product of the space-based system and the far distance between the radar and asteroid targets, the target signal is extremely weak. Prolonging the coherent accumulation time can effectively improve the radar detection capability of small asteroid targets, but the complex effects of range migration (RM) and Doppler frequency migration (DFM) will degrade the target coherent accumulation performance. To effectively solve this problem, an improved Keystone transform (KT) matched filtering banks method based on particle swarm optimization algorithm is proposed. Compared with traditional methods, the proposed method can not only ensure that the asteroid target detection performance is close to the theoretical optimum, but also reduce the system computation complexity. Simulation results verify the effectiveness of the proposed algorithm.

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