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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Ruixin Lai Xia Ai Shaoran Wang Mengmeng Li Jiaqi Liu Dazhi Ding School of Electronics and Optical Engineering Nanjing university of science and technology Nanjing China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

This paper proposes a method to identify micromotion parameters of radar echo with noise based on deep learning. The radar echo database is constructed from the point scattering model and the micro-Doppler spectrogram dataset is obtained then. The convolutional neural network is constructed to denoise radar echo with three kind of noises with different SNR, and target micro-motion parameters are identified.

关键词： Deep learning Parameter estimation Noise reduction Scattering Radar Speckle Radar scattering

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Adaptive-Correlation Back-Projection Imaging Algorithm for Ground Penetrating Radar in Complex Scenes

Adaptive-Correlation Back-Projection Imaging Algorithm for G...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Dai, Qianqi Lu, Gao Jiang, Tao Harbin Engineering University Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin150001 China Beijing Institute of Space Long March Vehicle National Key Laboratory of Science and Technology on Test Physics and Umerical Mathematics Beijing100076 China

ISBN: (纸本)9781665452366

The current correlation back-projection algorithm can only deal with the imaging of objects at the same buried depth. However, for objects with different depths and different relative permittivity, the electromagnetic wave echo composition is complicated, there is no strong correlation between the time delays of the reflected echoes, the echo signal in the center of the detection area is used as a reference signal to perform consistent correlation processing, which will cause serious suppression. In this paper, an improved adaptive correlation algorithm was proposed. Firstly, the algorithm of maximum variance between clusters (OSTU) is used to extract the horizontal position and number of buried objects, and then the relevant parameters are adaptively adjusted according to the reflected energy and horizontal position of different targets. Finally, back-projection algorithm imaging is performed. Simulation experiments showed that the algorithm proposed in this paper can effectively improve the imaging effect, improve the detection probability of buried objects, and adapt to the variability of detection scenes. © 2022 IEEE.

关键词： Ground penetrating radar systems

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Cooperative Jamming Resource Allocation Based on Artificial Bee Colony Multi-objective Decomposition

Cooperative Jamming Resource Allocation Based on Artificial ...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Lu, Gao Dai, Qianqi Xia, Jiechen Beijing Institute of Space Long March Vehicle National Key Laboratory of Science and Technology on Test Physics and Umerical Mathematics Beijing100076 China Ministry of Industry and Information Technology Harbin Engineering University Key Laboratory of Advanced Marine Communication and Information Technology Harbin150001 China

ISBN: (纸本)9781665452366

Electromagnetic countermeasure plays an important role in modern warfare. Cooperative jamming is one of the main means to counter radar network. In order to improve jamming efficiency, a jamming resource allocation algorithm based on artificial bee colony multi-target decomposition is proposed in this paper. The algorithm takes into account the interference effect and cost, and uses the decomposition mechanism to improve the search efficiency. The simulation results show that the allocation solution set obtained by this algorithm has good performance in diversity and spacing. © 2022 IEEE.

关键词： Resource allocation

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Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

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Advances in Atmospheric sciences 2023年第2期40卷 235-250页

作者： Jianguo LIU Zong-Liang YANG Binghao JIA Longhuan WANG Ping WANG Zhenghui XIE Chunxiang SHI School of Mathematics and Computational Science and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan ProvinceHuaihua UniversityHuaihuaHunan 418008China Department of Geological Sciences The John A.and Katherine G.Jackson School of GeosciencesUniversity of Texas at AustinAustinTexas 78712-1722USA State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were *** simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against *** results show that the meteorological forcing is the most important factor governing *** that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the *** Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight *** increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD *** study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

关键词： hydrological simulations land surface model meteorological forcing land surface parameters uncertainty

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Toward a Learnable Climate Model in the Artificial Intelligence Era

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Advances in Atmospheric sciences 2024年第7期41卷 1281-1288页

作者： Gang HUANG Ya WANG Yoo-Geun HAM Bin MU Weichen TAO Chaoyang XIE 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 University of Chinese Academy of Sciences Beijing 100049China Department of Environmental Planning Graduate School of Environmental StudiesSeoul National UniversitySeoul 08826South Korea School of Software Engineering Tongji UniversityShanghai 200092China

Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related *** this AI-driven transformation,the foundational role of physics in climate science has occasionally been *** perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”*** controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical ***,we provide illustrative examples to guide future assessments and constraints for AI *** AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online ***,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)*** a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.

关键词： artificial intelligence deep learning learnable climate model

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Piecewise Linear Recursive Convolution Method Applied in One-dimensional Unmagnetized Plasma

Piecewise Linear Recursive Convolution Method Applied in One...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Jiaqi Liu Gang Meng Lei Mu Lu Gao Jinjun Mo Runhui Wu Weidong Wang National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing China School of Information and Communication Guilin University of Electronic Technology Guilin China

The piecewise linear recursive convolution(PLRC) method based on finite difference time domain(FDTD) is used to calculate the reflection and transmission characteristics of electromagnetic waves from one-dimensional unmagnetized plasma. The results are shown that this method has obvious advantages in accurately calculating the electromagnetic problems of one-dimensional, small-scale and thin-layer dielectric materials.

关键词： Convolution Electromagnetic scattering Dielectric materials Computational electromagnetics Reflection Plasmas Electromagnetics

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The Warm Arctic-Cold Eurasia Pattern and Its key Region in Winter in CMIP6 Model Simulations

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Advances in Atmospheric sciences 2023年第12期40卷 2138-2153,I0002-I0006页

作者： Liang ZHAO Yunwen LIU Yihui DING Qingquan LI Wei DONG Xinyong SHEN Wei CHENG Haoxin YAO Ziniu XIAO State Key Laboratory of Numerical Modeling for Atmosphere Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China Neijiang Meteorological Bureau Neijiang 641000China China Meteorological Administration National Climate CenterBeijing 100081China Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou 310058China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China Beijing Institute of the Applied Meteorology Beijing 100029China

An enhanced Warm Arctic-Cold Eurasia(WACE)pattern has been a notable feature in recent winters of the Northern ***,divergent results between model and observational studies of the WACE still *** study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)in simulating the WACE pattern in winter of 1980-2014 and explores the key factors causing the differences in the simulation capability among the *** results show that the multimodel ensemble(MME)can better simulate the spatial distribution of the WACE pattern than most single *** that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well,especially the latter,usually can/cannot simulate the WACE pattern *** mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea-Kara seas(BKS)*** analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking(UB),which can transport heat to the BKS region,causing the warm Arctic,and strengthen the westerly trough downstream,cooling central ***,simulation of UB is key and significantly affects the model’s performance in simulating the WACE.

关键词： warm Arctic-cold Eurasia pattern Arctic amplification CMIP6 simulation evaluation extreme climate blocking highs

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Electroextraction of neodymium from LiCl-KCl melt using binary liquid Ga-Al cathode

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Journal of Rare Earths 2023年第8期41卷 1250-1257,I0005页

作者： Li Ding Xuepeng Wang Yongde Yan Valeri Smolenski Wenda Xu Alena Novoselova Yun Xue Fuqiu Ma Xingmei Zhang Key Laboratory of Superlight Materials and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001China Yantai Research Institute of Harbin Engineering University Yantai 264006China Institute of High-Temperature Electrochemistry UB RAS Ekaterinburg 620990Russia Department of Rare Metals and Nanomaterials Institute of Physics and TechnologyUral Federal UniversityEkaterinburg 620990Russia Yantai Standard Metrology Inspection&Test Center National Steam Flowrate Measurement StationYantai 264000China

The electrochemical behaviour of Nd(Ⅲ)ion was investigated on inert W,active Ga and Ga-AI *** is established that the reduction of Nd(Ⅲ)ion on the inert electrode is a consecutive two-step process while that on the active electrodes is a one-step *** apparent standard potential of the Nd(Ⅲ)/Nd redox couple at different temperatures was determined by open-circuit chronopotentiometry and semi-differential method,and the relationship between temperature and apparent standard potential was further *** thermodynamic properties of Nd in Ga and Ga-Al electrodes such as activity coefficient and activity were evaluated via intermittent coulomb titration and temperature dependence test,and the effect of temperature on activity coefficient was ***,Nd was successfully extracted in form of alloy from molten salt by galvanostatic electrolysis,in which the current efficiency of91.7%for the electroextraction indicates that the binary liquid Ga-Al electrode has favorable performance.

关键词： Rareearths Electroextraction Spent nuclear fuel Pyrochemical processing Lanthanides Binary liquid cathode

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A Radiation Pattern-Reconfigurable Patch Antenna with Tunable CSRR based on Liquid Metal and 3-D Printed Microfluidics

A Radiation Pattern-Reconfigurable Patch Antenna with Tunabl...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Yumeng Wang Lu Gao Pei Zheng Lingnan Song School of Electronic and Information Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

In this article, a radiation patternreconfigurable patch antenna with tunable complementary split-ring resonators (CSRR) based on liquid metal (LM) and 3-D printed microfluidics is presented. The antenna is composed of three layers, a top coaxial fed rectangular patch, a middle ground plane with two CSRRs etched symmetrically, and two bottom microfluidics channels each adhered underneath the corresponding CSRR. Pattern reconfiguration is achieved by filling the microfluidic channels with the liquid metal plugs to change the physical parameters of the CSRR structure. By adjusting the length of the slot stubs in CSRRs, the main beam of the double CSRR-loaded antenna can be continuously scanned from -46° to 46° in elevation plane.

关键词： Liquids Slot antennas Patch antennas Simulation Metals Filling Resonators

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Evaluation of multidimensional simulations of summer air temperature in China from CMIP5 to CMIP6 by the BCC models: From trends to modes

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Advances in Climate Change Research 2022年第1期13卷 28-41页

作者： Yun-Wen LIU Liang ZHAO Gui-Rong TAN Xin-Yong SHEN Su-Ping NIE Qing-Quan LI Li ZHANG Key Lciboratoiy of Meteorological Disaster Ministry of EducationJoint International Research Laboratory'of Climate and Environment ChangeCollaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Numerical Modeling for Atmosphere Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China Laboratory for Climate Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China

To determine whether the capability of the CMIP6 version of Beijing Climate Center(BCC)models(BCC-ESMI and BCC-CSM2-MR)in simulating China summer surface air temperature(SAT)has improved,we presented a multidimensional evaluation of the summer SAT in China including the trends,modes,and influencing *** comparisons are also made with the results of CMIP5(BCC-CSM1.1 and ***).In general,the CMIP6,especially BCC-CSM2-MR,has smaller deviations in the trends,the means,the mutations,the maximum centers,the variances,and the spatial patterns of the dominant modes from observatio relative to those of ***,the BCC CMIP6 models still underestimate the SAT variation in the Qinghai-Tibetan Plateau and the northeastern regions of China,and the performance is unsatisfactory with respect to the physical drivers of the dominant ***,all the BCC models can capture the spatio-temporal characteristics of the first mode well and can,in general,characterize the spatial pattern of the second mode,but none of the models perform well in the principal component of the second mode(PC2)due to the low performance with respect to the interannual variation of ***,the factors influencing the leading two modes are *** two CMIP6 can simulate better the Northern Hemisphere subtropical high northern boundary affecting the first *** factor,the Asia polar vortex area,can only be simulated better by two low-resolution models(BCC-CSM1.1 and BCC-ESM I).For the second mode,all four models simulate the influence of Asian zonal circulation well,but poorly simulate that of the southern Indian Ocean dipole due to a large deviation in the Indian Ocean surface temperature.

关键词： Summer mean temperature China Dominant mode CMIP6 BCC

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