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2021 CIE International Conference on Radar, Radar 2021

作者： Chang, Xin Li, Yanbin Zhao, Yan Du, Yufeng Liu, Donghui Wan, Jun Hebei Key Laboratory of Electromagnetic Spectrum Cognition and Control Shijiazhuang China Electronics Technology Group Shijiazhuang China School of Economics and Management Shijiazhuang Tiedao University Shijiazhuang China Chongqing Key Laboratory of Space Information Network and Intelligent School of Microelectronics and Communication Engineering Chongqing University Information Fusion Chongqing University Chongqing China

ISBN: (纸本)9781665498142

To reduce difficulty of obtaining jamming parameters, combining scattered wave deception jamming method structure with genetic algorithm, a scattered wave deceptive jamming method based on genetic algorithm is proposed against three Channel SAR GMTI. Four-dimensional jamming parameter searching problem is separated as a one-dimensional optimization problem and a two-dimensional optimization problem, which will reduce computational burden and jamming parameter acquirement time and raise fidelity of deceptive jamming. In addition, the problem, that tolerance of Doppler rate mismatch is difficult to describe, is solved by transforming an objective function of the two-dimensional optimization problem. By utilizing jamming quality parameters, simulation experiments are provided to verify the effectiveness of SGA method against the three-channel SAR GMTI. © 2021 IEEE.

关键词： deception jamming displaced phase center antenna (DPCA) genetic algorithm ground moving target indication (GMTI) scattered wave jamming synthetic aperture radar (SAR)

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Metal Influence Suppression Method for Rotating Wireless Power Transfer System Based on Toroidal Double-D Coil

Metal Influence Suppression Method for Rotating Wireless Pow...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Wenjiang Yuan Xian Zhang Lin Sha Tianjin Key Laboratory of Intelligent Control of Electrical Equipment Tiangong University Tianjin China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin China Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology Tianjin China

The wireless power transfer technology provides a feasible solution for scenarios where there is a demand for rotating power transfer. However, the rotating power transfer system is located in a small space and the design of each part is too compact, and when it is too close to the surrounding metal parts, the influence of the metal will cause the system parameters to change and reduce the energy transfer efficiency, and the eddy current loss generated in the metal will lead to temperature rise and affect the safe operation of the system. In this paper, we take an electrically excited motor as the application scenario, establish the equivalent influence model of the system lateral to the metal of different spacing and material, conduct circuit parameters and magnetic field analysis, and propose a toroidal DD structured coil for the design of wireless power transfer system according to the need to suppress the influence of metal and anti-rotation *** on the finite element method, a simulation model is established to analyze the transmission performance and the surrounding magnetic field of the toroidal DD coil under metal disturbance and to compare the metal influence and rotational offset resistance of the wireless power transfer Finally, an experimental platform of the rotating wireless power transfer system with a toroidal DD coil under the influence of metal at the end of the simulated motor is built to experimentally verify the theoretical and simulation models. The experimental results show that the proposed toroidal DD coil structure has better resistance to metal influence and rotational offset than other power transfer coil structures.

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Bayesian Non-parametric Hidden Markov Model for Agile Radar Pulse Sequences Streaming Analysis

arXiv

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arXiv 2023年

作者： Bao, Jiadi Li, Yunjie Zhu, Mengtao Wang, Shafei School of Information and Electronics Beijing Institute of Technology Beijing100081 China Peng Cheng Laboratory Shenzhen518055 China School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China The School of Information and Electronics Beijing Institute of Technology Beijing100081 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100191 China

—Multi-function radars are sophisticated types of sensors with the capabilities of complex agile inter-pulse modulation implementation and dynamic work mode scheduling. The developments in MFRs pose great challenges to modern electronic reconnaissance systems or radar warning receivers for recognition and inference of MFR work modes. To address this issue, this paper proposes an online processing framework for parameter estimation and change point detection of MFR work modes. At first, this paper designed a fully-conjugate Bayesian Non-Parametric Hidden Markov Model with a designed prior distribution (agile BNP-HMM) to represent the MFR pulse agility characteristics. Then, the proposed framework is constructed by two main parts. The first part is the agile BNP-HMM model for automatically inferring the number of HMM hidden states and emission distribution of the corresponding hidden states. An error lower bound is derived for estimation performance and the proposed algorithm is shown to be closer to the bound compared with baseline methods. The second part combines the streaming Bayesian updating to facilitate computation, and designed an online work mode change detection framework based upon the weighted sequential probability ratio test. We demonstrate that the proposed framework is consistently highly effective and robust to baseline methods on diverse simulated radar signal data and real-life benchmark datasets. Copyright © 2023, The Authors. All rights reserved.

关键词： Hidden Markov models

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Bipartite Containment control of Nonuniform Delayed Fractional-Order Multi-Agent Systems Over Signed Networks

Bipartite Containment Control of Nonuniform Delayed Fraction...

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IEEE Conference on Decision and control

作者： Weihao Li Kaiyu Qin Jinliang Shao Lei Shi Mengji Shi Wei Xing Zheng School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China School of Artificial Intelligence Henan University Zhengzhou China School of Computer Data and Mathematica Sciences Western Sydney University Sydney NSW Australia

In this study, the bipartite containment control problem of fractional-order multi-agent systems with nonuni-form time delays is addressed. An in-depth analysis of the system stability and bipartite containment control performance from a delay margin perspective is provided. Theoretically, the corresponding delay margin (maximum allowable time delay) over undirected and directed signed networks is obtained in the presence of nonuniform time delays, respectively. In addition, numerical relationships between the delay margin and the control coefficients, fractional order, and topology parameters are established, thus enabling easy and direct calculation of the maximum allowable time delay and facilitating distributed controller design and controller parameter tuning. Finally, some simulation examples are given to verify the effectiveness of the proposed bipartite containment controller and the obtained delay margin.

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Constrained Coverage of Unknown Environment Using Safe Reinforcement Learning

Constrained Coverage of Unknown Environment Using Safe Reinf...

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IEEE Conference on Decision and control

作者： Yunlin Zhang Junjie You Lei Shi Jinliang Shao Wei Xing Zheng School of Automation Engineering University of Electronic Science and Technology of China Chengdu China School of Artificial Intelligence Henan University Zhengzhou China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China School of Computer Data and Mathematical Sciences Western Sydney University Sydney NSW Australia

Achieving a connected, collision-free and time-efficient coverage in unknown environments is challenging for multi-agent systems. Particularly, agents with second-order dynamics are supposed to efficiently search and reach the optimal deployment positions over targets whose distribution is unknown, while preserving the distributed connectivity and avoiding collision. In this paper, a safe reinforcement learning based shield method is proposed for unknown environment exploration while correcting actions of agents for safety guarantee and avoiding invalid samples into policy updating. The shield is achieved distributively by a control barrier function and its validity is proved in theory. Moreover, policies of the optimal coverage are centrally learned via reward engineering and executed distributively. Numerical results show that the proposed approach not only achieves zero safety violations during training, but also speeds up the convergence of learning.

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Bipartite Flocking control for Multi-Agent Systems with Switching Topologies and Time Delays Under Coopetition Interactions

Bipartite Flocking Control for Multi-Agent Systems with Swit...

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IEEE Conference on Decision and control

作者： Zhuangzhuang Ma Bowen Li Jinliang Shao Yuhua Cheng Wei Xing Zheng School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China School of Computer Data and Mathematical Sciences Western Sydney University Sydney NSW Australia

This paper investigates the bipartite flocking behavior of multi-agent systems with coopetition interactions, where communications between agents are described by signed digraphs. The scenario with switching topologies due to the movement of agents, and time delays caused by the limited data transmission capability, is considered comprehensively. Nonlinear weight functions are designed to describe the relationship between the communication distance of agents and the coopetition degree in real biological networks. A distributed update rule based on the neighbors' information and the designed weight functions is proposed. By the aid of the graph theory and sub-stochastic matrix properties, the effectiveness of the proposed update rule is proved theoretically, and the algebraic conditions for achieving the bipartite flocking behavior are obtained. Finally, the theoretical results are verified by numerical simulations.

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Directly wireless communication of human minds via non-invasive brain-computer-metasurface platform

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eLight 2022年第1期2卷 132-142页

作者： Qian Ma Wei Gao Qiang Xiao Lingsong Ding Tianyi Gao Yajun Zhou Xinxin Gao Tao Yan Che Liu Ze Gu Xianghong Kong Qammer HAbbasi Lianlin Li Cheng‑Wei Qiu Yuanqing Li Tie Jun Cui Institute of Electromagnetic Space Southeast UniversityNanjing 210096China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China State Key Laboratory of Millimeter Wave Southeast UniversityNanjing 210096China Center of Intelligent Metamaterials Pazhou Laboratory Guangzhou 510330China Research Center for Brain-Computer Interface Pazhou LabGuangzhou 510330China Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore University of Glasgow James Watt School of EngineeringGlasgow G128QQUK State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsPeking UniversityBeijing 100871China

Brain-computer interfaces(BCIs),invasive or non-invasive,have projected unparalleled vision and promise for assisting patients in need to better their interaction with the *** by the BCI-based rehabilitation technologies for nerve-system impairments and amputation,we propose an electromagnetic brain-computer-metasurface(EBCM)paradigm,regulated by human’s cognition by brain signals directly and *** experimentally show that our EBCM platform can translate human’s mind from evoked potentials of P300-based electroencephalography to digital coding information in the electromagnetic domain non-invasively,which can be further processed and transported by an information metasurface in automated and wireless *** wireless communications of the human minds are performed between two EBCM operators with accurate text ***,several other proof-of-concept mind-control schemes are presented using the same EBCM platform,exhibiting flexibly-customized capabilities of information processing and synthesis like visual-beam scanning,wave modulations,and pattern encoding.

关键词： communication computer surface

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Sea-Net:Visual cognition-enabled Sample and Embedding Adaptive Network for SAR Image Object Classification

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2023年 1-14页

作者： Fan, Lili Zeng, Changxian Liu, Hongmei Liu, Jianjian Li, Yunjie Cao, Dongpu School of Information and Electronics Beijing Institute of Technology Jiangsu Industrial Innovation Center of Intelligent Equipment Co. Ltd Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China School of Science Dalian Minzu University Dalian China Automotive Engineering Research Institute BYD Automotive Industry Co. Ltd Shenzhen China School of Information and Electronices Beijing Institute of Technology Beijing China School of Vehicle and Mobility Tsinghua University Beijing China

In autonomous driving, the perception module typically utilizes a combination of millimeter-wave radar and LiDAR. However, when driving in challenging environmental conditions, this perception combination fails to effectively acquire geometric shape information about the surrounding environment. Therefore, we propose an alternative perception approach that employs Synthetic Aperture Radar (SAR). However, existing algorithms heavily rely on large-scale datasets. In light of this, we propose a meta-learning framework, named Sample and Embedding Adaptive Network (Sea-Net), for few-shot SAR image object classification. Furthermore, the semantics of SAR images and traditional optical images differ, and thus data enhancement methods that are effective on optical images are less so on SAR images. Based on this observation, we introduce a self-adaptive augmentation algorithm for the center of the target domain, which performs self-adaptive augmentation based on the semantic features of SAR images. The entire enhancement stage can be parallelized to speed up computation. Moreover, the imaging principle of SAR image results in coherent speckle noise with bright and dark interlacing in the image, causing a small difference between classes in the SAR image mapped to the embedded space. To address this issue, we propose the edge ambiguous embedding correction based on the self-attention mechanism. This method effectively increases the distance between different classes. Our experimental results on the MSTAR dataset demonstrate that the proposed model outperforms existing methods. IEEE

关键词： Radar imaging

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Infrared Video Data Cleaning Based on LightWeight CNN-LSTM

Infrared Video Data Cleaning Based on LightWeight CNN-LSTM

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Chinese Automation Congress (CAC)

作者： Fang Liu Shiwei Li Congang Chen Yutong Hu Hua Gong Liaoning Key Laboratory of Intelligent Optimization and Control for Ordnance Industry College of Science Shengyang Ligong University Shenyang China School of Automation and Electrical Engineering Shengyang Ligong University Shenyang China Faculty of Science and Technology Beijing Normal University - Hong Kong Baptist University United International College Zhuhai China National Key Laboratory of Electromagnetic Space Security Tianjing China

Video cleaning is a pivotal technology for enhancing the quality of infrared video data. In order to achieve high-quality cleaning of infrared video data, the temporal correlation features in the video data are thoroughly taken into account. A feature extraction model is designed. This model integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory Networks (LSTM). It can extract infrared video features in both spatial dimension and temporal dimension. Considering the characteristics of low resolution and weak feature information in infrared video images, a lightweight strategy is adopted to achieve high-quality extraction of weak information in infrared images. In this paper, an infrared video data cleaning model lightweight CNN-LSTM is developed by incorporating a lightweight strategy and video spatiotemporal features. Through seven experimental comparisons, the model utilized in this study achieved improvement ranges of 0.6% to 43.8% in accuracy and 0.7% to 65.7% in recall.

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Heterogeneous microstructure and mechanical behaviour of Al-8.3Fe-1.3V-1.8Si alloy produced by laser powder bed fusion

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Virtual and Physical Prototyping 2023年第1期18卷 Article: e2155197页

作者： Yu, S.J. Wang, P. Li, H.C. Setchi, R. Wu, M.W. Liu, Z.Y. Chen, Z.W. Waqar, S. Zhang, L.C. Additive Manufacturing Institute Shenzhen University Shenzhen China Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robotics College of Mechatronics and Control Engineering Shenzhen University Shenzhen China School of Materials Science and Engineering Shanghai University of Engineering Science Shanghai China Cardiff School of Engineering Cardiff University Cardiff United Kingdom Department of Materials and Mineral Resources Engineering National Taipei University of Technology Taipei Taiwan Department of Mechanical Engineering Institute of Space Technology Islamabad Pakistan School of Engineering Edith Cowan University Perth Australia

The relationship between processing parameters, microstructure, and mechanical properties of Al-8.3Fe-1.3V-1.8Si alloy processed by laser powder bed fusion is seldom studied. Therefore, fully dense alloys with two parameters were selected to investigate this key issue. The results show that the alloy with low power and scanning speed (S200) shows fan-shell-shaped melt pools and laser tracks while another (S350) shows a deeper and wider melt pool. Both alloys obtain a heterogeneous microstructure without a secondary phase in melt pool (MP) and a nano-sized phase in melt pool boundary (MPB). The difference between solid-solution strengthening and Orowan strengthening in MP and MPB contributes to the difference in compressive yield strength (S200: 380 ± 14 MPa and S350: 705 ± 16 MPa), and heterogeneous nano-hardness results in different crack behaviours and failure strains. This work indicates that adjusting processing parameters is an effective method to control microstructure and mechanical properties of this alloy. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Aluminum alloys

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