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IEEE International Workshop on Electromagnetics, Applications and Student Innovation (iWEM)

作者： Shi Xiaofei Shi Jiaxin Liu Jiaqi Fang Zhongyi Wang Lei Song Lizhong Shandong Institute of Space Electronic Technology Yantai China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Information Science and Engineering Harbin Institute of Technology at Weihai Weihai China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China Shandong Huayu Aerospace Technology Co. Ltd Yantai China

This paper designs an array antenna with a planar printed structure. The antenna element adopts a rectangular slot antenna, and the antenna element is excited by a T-shaped feeding structure. The microstrip power distribution network is used to feed the antenna radiator array with equal power. The microstrip power distribution network and slot radiator array are located on top and bottom of dielectric substrate, and the array antenna is implemented by use of the printed circuit technology. In order to improve the gain, a metal reflector ground is placed below the dielectric substrate. A planar printed slot array antenna working in X band is designed. The coaxial line is used to feed the array antenna at the bottom. The whole antenna structure is easy to feed and suitable for fabrication. The designed array antenna was numerically calculated using full wave electromagnetic simulation software. At a working frequency of 10.1GHz, the voltage standing wave ratio (VSWR) of the antenna is about 1.35, and the gain is about 21.46dB. The design of the antenna scheme can be used as a reference for the actual application of engineering.

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A multi-agent jamming decision-making method based on SP-HASAC

A multi-agent jamming decision-making method based on SP-HAS...

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IET International Radar Conference (IRC 2023)

作者： Jingpeng Gao Chen Shen Lu Gao Zhiye Jiang College of Information and Communication Engineering Harbin Engineering University Harbin People's Republic of China Beijing Institute of Electronic System Engineering Beijing People's Republic of China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing People's Republic of China

ISBN: (数字)9781837240982

In the study of the multi-UAV penetration mission decision method, the Heterogeneous Agent Soft Actor-Critic algorithm uses the HAML framework and the maximum entropy principle to enable UAVs to have stronger anti-jamming capability and exploration capability. However, it is difficult to accurately evaluate the action value of UAVs and the training stability is poor. To address this issue, this paper proposes a multi-agent based on the state prediction-HASAC (SP-HASAC) jamming decision method. Based on the idea of advantage function decomposition and environmental dynamics model, the state prediction network is designed to extract more abundant spatial information of penetration battlefield and achieve accurate evaluation of the action value of multi-UAV. Combining with the negative domain activation theory, the ReLU function is improved to realize the stable training of multi-UAV. The simulation results show that in the electronic penetration scenario of three UAVs against a single radar, the training convergence time of the proposed improved algorithm is reduced by 22% compared with the original algorithm. Three UAVs penetration to twice the burn-through distance still has more than 70% penetration success rate.

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Design of a Printed Monopole Array Antenna with the Simple Feeding Structure

Design of a Printed Monopole Array Antenna with the Simple F...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Shi Xiaofei Liu Yizhuo Liu Jiaqi Fang Yizhong Gao Zhiwei Wang Lei Song Lizhong Shandong Institute of Space Electronic Technology Yantai China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Information Science and Engineering Harbin Institute of Technology at Weihai Weihai China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China School of Information Science and Technology Shijiazhuang Tiedao University Shijiazhuang China Shandong Huayu Aerospace Technology Co. Ltd Yantai China

This paper introduces an array antenna by use of printed monopole antennas as element. The designed array antenna consists of two layers of dielectric substrate and a metal reflective ground. The array antenna element adopts trapezoidal printed monopole antenna, and the element is fed by coplanar waveguide (CPW). The array antenna radiator is located on the top of the upper dielectric substrate, and the feeding microstrip power divider network is located on the bottom of the lower dielectric substrate. The antenna element radiator is vertically connected to the microstrip feeding power divider network in a coaxial-like manner. The whole structure of the antenna is simple, and the feeding structure is convenient, which makes it suitable for fabrication and assembly. A printed 4x4 monopole array antenna was designed and the relevant simulated results are provided. The simulation results show that at the 10GHz, the designed array antenna has a gain of approximately 12.73 dB and a return loss of approximately -11.75 dB. The antenna scheme discussed in this paper can provide technical reference for the design of planar printed array antennas.

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Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

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Advances in Atmospheric sciences 2024年第7期41卷 1299-1312页

作者： Ya WANG Gang HUANG Baoxiang PAN Pengfei LIN Niklas BOERS Weichen TAO Yutong CHEN BO LIU Haijie LI State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China Earth System Modelling School of Engineering and DesignTechnical University of MunichOttobrunn 85521Germany Potsdam Institute for Climate Impact Research Potsdam 14412Germany Department of Mathematics and Global Systems Institute University of ExeterExeter EX44QEUK CMA Earth System Modeling and Prediction Centre(CEMC) Chinese Academy of Meteorological SciencesBeijing 100081China

Climate models are vital for understanding and projecting global climate change and its associated ***,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future *** these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning ***,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST ***,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to ***,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to *** enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales *** study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

关键词： generative adversarial networks model bias deep learning El Niño-Southern Oscillation marine heatwaves

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A method for feature extraction based on SVD and machine learning

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IOP Conference Series: Materials science and Engineering 2019年第5期569卷

作者： Wei Mao Shuxian Huang Xin Liu Hongyan Liu Jiaqi Liu Yi Shu National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics 100076 China Beijing Institute of Precision Mechatronics and Controls 100076 China Beijing Institute of Long March Vehicle 100076 China

By studying the shortcomings of feature, which extracted from Radar-Cross Section(RCS),using mathematical and statistical method, using the idea of extracting abstract features in image recognition and speech recognition by artificial intelligence for reference[2][3]. This paper explores the possibility of extracting abstract features of target's RCS sequence, and proposes an abstract feature extraction method of RCS sequence based on singular value decomposition(SVD) feature decomposition. Because of the poor interpretability of abstract features, four different machine learning algorithms are used to classify the extracted Abstract features. The experimental results show that the machine learning algorithm can classify different types of spatial objects with high accuracy, which shows that the RCS features of different spatial objects can be characterized by abstract features.

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Resolved magnetohydrodynamic wave lensing in the solar corona

arXiv

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arXiv 2024年

作者： Zhou, Xinping Shen, Yuandeng Yuan, Ding Keppens, Rony Zhao, Xiaozhou Fu, Libo Tang, Zehao Wang, Jiaoyang Zhou, Chengrui College of Physics and Electronic Engineering Sichuan Normal University Chengdu610068 China Yunnan Observatories Chinese Academy of Sciences Kunming650216 China Shenzhen Key Laboratory of Numerical Prediction for Space Storm Institute of Space Science and Applied Technology Harbin Institute of Technology Guangdong Shenzhen China Key Laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences Beijing China Centre for mathematical Plasma Astrophysics Department of Mathematics KU Leuven Celestijnenlaan 200B LeuvenB-3001 Belgium

Electromagnetic wave lensing, a common physical phenomenon recognized in visible light for centuries, finds extensive applications in manipulating light in optical systems such as telescopes and cameras. Magnetohydrodynamic wave is a common perturbation phenomenon in the corona. By using high spatio-temporal resolution observations from the Solar Dynamics Observatory, here, we report the observation of a magnetohydrodynamic wave lensing in the highly ionized and magnetized coronal plasma, where quasi-periodic wavefronts emanated from a flare converged at a specific point after traversing a coronal hole. The entire process resembles an electromagnetic wave lensing from the source to the focus. Meanwhile, the magnetohydrodynamic wave lensing is well reproduced through a magnetohydrodynamic numerical simulation with full spatio-temporal resolution. We further investigate potential applications for coronal seismology, as the lensing process encodes information on the Alfvén speed, in conjunction with favorable geometric and density variations. Copyright © 2024, The Authors. All rights reserved.

关键词： Electromagnetic waves

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Graph-GIC: A Smart and Parallelized Geomagnetically Induced Current Modelling Algorithm Based on Graph Theory for Space Weather Applications

arXiv

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arXiv 2024年

作者： Chen, Wen Yuan, Ding Feng, Xueshang Poedts, Stefaan Zou, Zhengyang Feng, Song Zhu, Yuxuan Yin, Tong Shenzhen Key Laboratory of Numerical Prediction for Space Storm School of Aerospace Harbin Institute of Technology Guangdong Shenzhen518055 China Key Laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences Beijing China Centre for Mathematical Plasma Astrophysics Department of Mathematics KU Leuven LeuvenB-3001 Belgium State Key Laboratory of Lunar and Planetary Sciences Macau University of Science and Technology China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Institute of Physics University of Maria Curie-Sklodowska ul. Marii Curie-Sklodowskiej 1 Lublin20-031 Poland

Geomagnetically Induced Current (GIC) refers to the electromagnetic response of the Earth and its conductive modern infrastructures to space weather and would pose a significant threat to high-voltage power grids designed for the alternative current operation. To assess the impact of space weather on the power grid, one needs to calculate the GIC on a national or continental scale. In this study, we developed a smart and parallelized GIC modelling algorithm, Graph GIC. This algorithm deploys a graph representing a power grid in a single-line diagram, in which substations/transformers act as nodes and transmission lines as edges. With these denotations, a power grid and its electric parameters are mathematically represented with an adjacency matrix and an admittance matrix. We used sparse matrix and parallelisation techniques to expedite the intensive computation in cases of large-scale power grids. The Graph GIC was validated with a benchmark grid, applied to the GIC calculation of the 500 kV power grid of Guangdong, China, and conducted preliminary analysis on the grid’s susceptibility to geomagnetic storms. The Graph GIC algorithm has the advantage of an intuitive and highly scalable graph representation of a power grid at any scale. It achieves high-accuracy calculation and a speedup of about 18 times after parallelisation. This algorithm could be applied to assess the impact of space weather on a power grid up to continental scales and could be incorporated into global space weather modelling frameworks. Copyright © 2024, The Authors. All rights reserved.

关键词： Matrix algebra

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Author Correction: Transverse oscillations and an energy source in a strongly magnetized sunspot

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Nature Astronomy 2024年 674页

作者： Ding Yuan Libo Fu Błażej Kuźma Xueshang Feng Wenda Cao Michaël Geeraerts Tom Van Doorsselaere Juan C. Trelles Arjona Carlos Quintero Noda Basilio Ruiz Cobo Kris Murawski Abhishek K. Srivastava Yuhu Miao Song Feng Jiangtao Su Institute of Space Science and Applied Technology Harbin Institute of Technology Shenzhen Guangdong China Key Laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences Beijing China Shenzhen Key Laboratory of Numerical Prediction for Space Storm Harbin Institute of Technology Shenzhen Guangdong China Big Bear Solar Observatory New Jersey Institute of Technology Big Bear City CA USA Center for Solar-Terrestrial Research New Jersey Institute of Technology Newark NJ USA Centre for mathematical Plasma Astrophysics Mathematics Department KU Leuven Leuven Belgium Instituto de Astrofísica de Canarias (IAC) San Cristóbal de La Laguna Tenerife Spain Dept. Astrofísica Universidad de La Laguna San Cristóbal de La Laguna Tenerife Spain Institute of Physics University of M. Curie-Skłodowska Lublin Poland Department of Physics Indian Institute of Technology (BHU) Varanasi India School of Information and Communication Shenzhen Institute of Information Technology Shenzhen Guangdong China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming Yunnan China National Astronomical Observatories Chinese Academy of Sciences Beijing China School of Astronomy and Space Sciences University of Chinese Academy of Sciences Beijing China

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