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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Zheng, Ran Chen, Yuan S Zhang, Yu X Guo, Lei Bai, Liang J Zhang, Ping L Zhang, Ran National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle No. 1 Nanda Hongmen Road of Fengtai District Beijing China

ISBN: (纸本)9781728123455

The phase-switched screen (PSS) has been proved effective in the application of shielding a target or deceiving the radar system when the modulation frequency of it is set greater or smaller than the signal bandwidth. This paper analyses impacts of false targets generated by PSS (PSS-decoys) echoes on radar constant false alarm rate detection. The generation principle of PSS-decoys and the key factors that influence the signatures of PSS-decoys are introduced briefly at first. On base of it, the detection cost caused by the false alarm and false dismissal in a search period of radar is chosen as the criteria of detection performance. The detection costs of CA-CFAR, OS-CFAR, CMLD-CFAR detectors under multiple decoys jamming environment are analysed. Specially, we investigate the influence of the PSS key factors on detection costs from the perspective of simulation. The results show that detection costs will increase remarkably due to false targets existing and it is sensitive to the switching frequency, and the relationship to the duty ratio is tightly relevant to SNR. Among three detectors, the detection costs of CMLD-CFAR detector are higher than that of adopting CA-CFAR and that of adopting OS-CFAR. © 2019 IEEE.

关键词： Signal detection

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A Direct Position Determination Method for Four-station TDOA Location System

A Direct Position Determination Method for Four-station TDOA...

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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Qi, Sun-Rui Yuan, Chen-Shun Liang, Bai-Jin Gao-Lu Li-Hu Sun-Heng BEIJING INSTITUTE of SPACE LONG MARCH VEHICLE National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing100076 China

ISBN: (纸本)9781728123455

Aiming at the four-station networked TDOA (Time Difference of Arrival) localization system, a direct location method based on electronic elevation map search is proposed, the Geometric Dilution Precision (GDOP) is derived, and the factors affecting the location accuracy are analyzed. The location method under real conditions is also simulated, and its feasibility is demonstrated, which provides a new engineering method for networked TDOA location. © 2019 IEEE.

关键词： Time difference of arrival

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Single-Shot Intensity- and Phase-Sensitive Compressive Sensing-Based Coherent Modulation Ultrafast Imaging

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Physical Review Letters 2024年第17期132卷 173801-173801页

作者： Chengzhi Jin Yingming Xu Dalong Qi Yunhua Yao Yuecheng Shen Lianzhong Deng Ruozhong Han Zhen Pan Jiali Yao Yilin He Zhengqi Huang Xingchen Pan Hua Tao Mingying Sun Cheng Liu Junhui Shi Jinyang Liang Zhiyong Wang Jianqiang Zhu Zhenrong Sun Shian Zhang State Key Laboratory of Precision Spectroscopy School of Physics and Electronic Science East China Normal University Shanghai 200241 China Key Laboratory of High Power Laser and Physics Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 China Research Center for Humanoid Sensing Zhejiang Lab Hangzhou 311100 China Laboratory of Applied Computational Imaging Centre Énergie Matériaux Télécommunications Institut National de la Recherche Scientifique Varennes Québec J3X1S2 Canada School of Mathematical Sciences University of Electronic Science and Technology of China Chengdu 611731 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan 030006 China Joint Research Center of Light Manipulation Science and Photonic Integrated Chip of East China Normal University and Shandong Normal University East China Normal University Shanghai 200241 China

Ultrafast imaging can capture the dynamic scenes with a nanosecond and even femtosecond temporal resolution. Complementarily, phase imaging can provide the morphology, refractive index, or thickness information that intensity imaging cannot represent. Therefore, it is important to realize the simultaneous ultrafast intensity and phase imaging for achieving as much information as possible in the detection of ultrafast dynamic scenes. Here, we report a single-shot intensity- and phase-sensitive compressive sensing-based coherent modulation ultrafast imaging technique, shortened as CS-CMUI, which integrates coherent modulation imaging, compressive imaging, and streak imaging. We theoretically demonstrate through numerical simulations that CS-CMUI can obtain both the intensity and phase information of the dynamic scenes with ultrahigh fidelity. Furthermore, we experimentally build a CS-CMUI system and successfully measure the intensity and phase evolution of a multimode Q-switched laser pulse and the dynamical behavior of laser ablation on an indium tin oxide thin film. It is anticipated that CS-CMUI enables a profound comprehension of ultrafast phenomena and promotes the advancement of various practical applications, which will have substantial impact on fundamental and applied sciences.

关键词： Ultrafast optics Imaging & optical processing

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Topology Optimization of Complex Network based on NSGA-II 4

Topology Optimization of Complex Network based on NSGA-II

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4th IEEE Advanced Information technology, Electronic and Automation Control Conference, IAEAC 2019

作者： Bin, Zhang Gan, Zhi-Chun Wen, Chen Hu, Qiang-Qiang Hou, Jian-Feng National University of Defense Technology Departments of Information and Communication China Science and Technology on Test Physics Numerical Mathematic Laboratory China

ISBN: (纸本)9781728119076

This paper proposes a complex network topology optimization method based on NSGA-II with degrees and edges number unchanged. The method selects the elite parent networks by applying non-dominated layer sorting and congestion degree calculation through the network crossover and mutation operation to achieve maximum network efficiency and network invulnerability. Simulation analysis shows that the method can significantly improve the invulnerability and network efficiency of the initial networks at the same time. Optimizing the network efficiency makes the network connection show a negative correlation. The network presents a "multi-core decentralized" structure;optimizing the network invulnerability makes the connection show a positive correlation, the network presents a "close core and scattered periphery" structure;the cooperative optimization makes the network present a "tighter core and large periphery" structure, which is proved with good theoretical generality and practical application value. © 2019 IEEE.

关键词： Complex networks

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DRUM: Diffusion-based runoff model for probabilistic flood forecasting

arXiv

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arXiv 2024年

作者： Ou, Zhigang Nai, Congyi Pan, Baoxiang Pan, Ming Shen, Chaopeng Jiang, Peishi Liu, Xingcai Tang, Qiuhong Li, Wenqing Zheng, Yi School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen China Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric Physics Chinese Academy of Science Beijing China Scripps Institution of Oceanography University of California La Jolla San DiegoCA United States Civil and Environmental Engineering The Pennsylvania State University University ParkPA United States Atmospheric Climate and Earth Sciences Division Pacific Northwest National Laboratory RichlandWA United States Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China State Key Laboratory of Stimulation and Regulation of Water Cycles in River Basins China Institute of Water Resources and Hydropower Research Beijing China

Reliable flood forecasting remains a critical challenge due to persistent underestimation of peak flows and inadequate uncertainty quantification in current approaches. We present DRUM (Diffusion-based Runoff Model), a generative AI solution for probabilistic runoff prediction. DRUM builds up an iterative refinement process that generates ensemble runoff estimates from noise, guided by past meteorological conditions, present meteorological forecasts, and static catchment attributes. This framework allows learning complex hydrological behaviors without imposing explicit distributional assumptions, particularly benefiting extreme event prediction and uncertainty quantification. Using data from 531 representative basins across the contiguous United States, DRUM outperforms state-of-the-art deep learning methods in runoff forecasting regarding both deterministic and probabilistic skills, with particular advantages in extreme flow (1%) predictions. DRUM demonstrates superior flood early warning skill across all magnitudes and lead times (1–7 days), achieving F1 scores near 0.4 for extreme events under perfect forecasts and maintaining robust performance with operational forecasts, especially for longer lead times and high-magnitude floods. When applied to climate projections through the 21st century, DRUM reveals increasing flood vulnerability in 47.8–57.1% of basins across emission scenarios, with particularly elevated risks along the West Coast and Southeast regions. These advances demonstrate significant potential for improving both operational flood forecasting and long-term risk assessment in a changing climate. © 2024, CC BY-NC-SA.

关键词： Floods

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A Physical Layer key Generation method with Reliable Negotiation

A Physical Layer Key Generation method with Reliable Negotia...

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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Wang, Yuchen Wu, Xuanli Xu, Zhicong Wu, Wei Li, Hu Zhang, Ran School of Electronics and Information Engineering Harbin Institude of Technology Harbin China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9781728123455

There is a risk of information leakage in the process of wireless communication. The introduction of key generation in the physical layer can effectively improve the security of wireless communication. This paper proposes a new physical layer key generation method in the TDD (time division duplex) communication system. Assume that the uplink and downlink channels are reciprocal. Through LDPC (Low Density Parity Check)channel coding and negotiation algorithm, the inconsistency rate of key generation between Alice and Bob is reduced. Simulation and analysis results show that the method improves the key generation rate and reduces the key inconsistency rate. © 2019 IEEE.

关键词： Hash functions

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Design of Non-uniform Flexible Meta-surface for Antenna Beam-steering

Design of Non-uniform Flexible Meta-surface for Antenna Beam...

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IEEE International Conference on Electronic Information and Communication technology (ICEICT)

作者： Yuwei Qiu Zhiye Jiang Pei Zheng School of Electronic Information Northwestern Polytechnical University Xi'an China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing China

ISBN: (数字)9781728190457

ISBN: (纸本)9781728190464

Design of non-uniform flexible meta-surface for antenna beam-steering is presented in this paper. By properly tuning the dimensions of quasi-I-shaped unit cells on meta-surface, we propose a bi-layer meta-surface that can achieve beam deflection of up to 34°. Horn antenna is adopted as the feed antenna to illuminate the meta-surface which is printed on flexible plastic sheet. The meta-surface is fixed on the outside surface of horn antenna with an electric motor, making it possible to slide relative to the aperture of feed antenna. The horn antenna together with the meta-surface will work like a projector when operating, the main-beam of the horn antenna can be steered when different frames of the meta-surface cover the horn aperture and the steering range is ±34°. Radiation reconfigurable is thus achieved through a simple structure. Prototype will be fabricated in the following research.

关键词： Horn antennas Prototypes Antenna feeds Aperture antennas Information and communication technology Plastics Tuning

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Record High Temperatures in the Ocean in 2024

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Advances in Atmospheric sciences 2025年第6期42卷 1092-1109页

作者： Lijing CHENG John ABRAHAM Kevin E.TRENBERTH James REAGAN Huai-Min ZHANG Andrea STORTO Karina VON SCHUCKMANN Yuying PAN Yujing ZHU Michael E.MANN Jiang ZHU Fan WANG Fujiang YU Ricardo LOCARNINI John FASULLO Boyin HUANG Garrett GRAHAM Xungang YIN Viktor GOURETSKI Fei ZHENG Yuanlong LI Bin ZHANG Liying WAN Xingrong CHEN Dakui WANG Licheng FENG Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Gengxin CHEN Rongwang ZHANG Alexey MISHONOV Zhetao TAN Wangxu WEI Huifeng YUAN Guancheng LI Qiuping REN Lijuan CAO Yayang LU Juan DU Kewei LYU Albertus SULAIMAN Michael MAYER Huizan WANG Zhanhong MA Senliang BAO Henqian YAN Zenghong LIU Chunxue YANG Xu LIU Zeke HAUSFATHER Tanguy SZEKELY Flora GUES National Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of St.Thomas School of EngineeringMinnesota 55105USA NSF National Center for Atmospheric Research BoulderColorado 80307USA University of Auckland Auckland 0630New Zealand National Oceanic and Atmospheric Administration National Centers for Environmental InformationSilver SpringMaryland 20910USA National Oceanic and Atmospheric Administration National Centers for Environmental InformationAshevilleNC 28801USA National Research Council(CNR)Institute of Marine Sciences(ISMAR) Rome 00133Italy Mercator Ocean International Toulouse 31400France Department of Earth and Environmental Science University of PennsylvaniaPhiladelphiaPennsylvania 19104USA Institute of Oceanology Chinese Academy of SciencesQingdao 266071China National Marine Environmental Forecasting Center Ministry of Natural Resources of ChinaBeijing 100081China North Carolina Institute for Climate Studies(NCICS) North Carolina State UniversityAshevilleNC 28804USA Oceanographic Data Center Chinese Academy of SciencesQingdao 266071China College of Oceanography Hohai UniversityNanjing 210098China National Marine Data and Information Service Tianjin 300171China Istituto Nazionale di Geofisica e Vulcanologia Sede di BolognaBologna 40128Italy South China Sea Institute of Oceanology Chinese Academy of SciencesGuangzhou 510301China ESSIC/CISESS-MD University of MarylandCollege ParkMD 20740USA Computer Network Information Center Chinese Academy of SciencesBeijing 100083China Eco-Environmental Monitoring and Research Center Pearl River Valley and South China Sea Ecology and Environment AdministrationMinistry of Ecology and EnvironmentGuangzhou 510611China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Xiamen Universit

Heating in the ocean has continued in 2024 in response to increased greenhouse gas concentrations in the atmosphere,despite the transition from an El Ni?o to neutral conditions. In 2024, both global sea surface temperature(SST) and upper2000 m ocean heat content(OHC) reached unprecedented highs in the historical record. The 0–2000 m OHC in 2024exceeded that of 2023 by 16 ± 8 ZJ(1 Zetta Joules = 1021 Joules, with a 95% confidence interval)(IAP/CAS data), which is confirmed by two other data products: 18 ± 7 ZJ(CIGAR-RT reanalysis data) and 40 ± 31 ZJ(Copernicus Marine data,updated to November 2024). The Indian Ocean, tropical Atlantic, Mediterranean Sea, North Atlantic, North Pacific, and Southern Ocean also experienced record-high OHC values in 2024. The global SST continued its record-high values from2023 into the first half of 2024, and declined slightly in the second half of 2024, resulting in an annual mean of 0.61°C ±0.02°C(IAP/CAS data) above the 1981–2010 baseline, slightly higher than the 2023 annual-mean value(by 0.07°C ±0.02°C for IAP/CAS, 0.05°C ± 0.02°C for NOAA/NCEI, and 0.06°C ± 0.11°C for Copernicus Marine). The record-high values of 2024 SST and OHC continue to indicate unabated trends of global heating.

关键词： ocean heat content sea surface temperature ocean temperature global warming climate

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Contributions to the Interannual Summer Rainfall Variability in the Mountainous Area of Central China and Their Decadal Changes

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Advances in Atmospheric sciences 2020年第3期37卷 259-268页

作者： Kaiming HU Yingxue LIU Gang HUANG Zhuoqi HE Shang-Min LONG Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Joint Center for Global Change Studies(JCGCS) Beijing 100875China University of Chinese Academy of Sciences Beijing 100049China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China State Key Laboratory of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China College of Oceanography Hohai UniversityNanjing 210098China

Using a high-resolution precipitation dataset,the present study detected that the mountainous area of central China(MACA)is a hotspot of ENSO’s impact on the summer rainfall *** analysis suggests that both ENSO and atmospheric forcing make contributions to the summer rainfall variability in *** dominant rainfall-related SST mode features as a seasonal transition from an El Niño-like warming in the preceding winter to a La Nina-like cooling in the following autumn,and it explains about 29%of the total variance of the rainfall during 1951–*** indicates that ENSO with a rapid phase transition is responsible for inducing summer rainfall anomalies in ***,an upperlevel circumglobal wave mode in the Northern Hemisphere during summer also explains about 29%of the summer rainfall *** of both the SST and the atmospheric modes have experienced interdecadal *** influence of the SST mode gradually increases and plays a dominant role in the recent decades,suggesting that ENSO with a rapid phase transition becomes more important for rainfall prediction in MACA.

关键词： summer rainfall ENSO atmospheric internal variability interdecadal change

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Record High Temperatures in the Ocean in 2024

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Advances in Atmospheric sciences 2025年第6期 1092-1109页

作者： Lijing CHENG John ABRAHAM Kevin E.TRENBERTH James REAGAN Huai-Min ZHANG Andrea STORTO Karina VON SCHUCKMANN Yuying PAN Yujing ZHU Michael E.MANN Jiang ZHU Fan WANG Fujiang YU Ricardo LOCARNINI John FASULLO Boyin HUANG Garrett GRAHAM Xungang YIN Viktor GOURETSKI Fei ZHENG Yuanlong LI Bin ZHANG Liying WAN Xingrong CHEN Dakui WANG Licheng FENG Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Gengxin CHEN Rongwang ZHANG Alexey MISHONOV Zhetao TAN Wangxu WEI Huifeng YUAN Guancheng LI Qiuping REN Lijuan CAO Yayang LU Juan DU Kewei LYU Albertus SULAIMAN Michael MAYER Huizan WANG Zhanhong MA Senliang BAO Henqian YAN Zenghong LIU Chunxue YANG Xu LIU Zeke HAUSFATHER Tanguy SZEKELY Flora GUES National Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of Sciences University of St. Thomas School of Engineering NSF National Center for Atmospheric Research University of Auckland National Oceanic and Atmospheric Administration National Centers for Environmental Information National Research Council (CNR) Institute of Marine Sciences (ISMAR) Mercator Ocean International Department of Earth and Environmental Science University of Pennsylvania Institute of Oceanology Chinese Academy of Sciences National Marine Environmental Forecasting Center Ministry of Natural Resources of China North Carolina Institute for Climate Studies (NCICS) North Carolina State University Oceanographic Data Center Chinese Academy of Sciences College of Oceanography Hohai University National Marine Data and Information Service Istituto Nazionale di Geofisica eVulcanologia Sede di Bologna South China Sea Institute of Oceanology Chinese Academy of Sciences ESSIC/CISESS-MD University of Maryland Computer Network Information Center Chinese Academy of Sciences Eco-Environmental Monitoring and Research Center Pearl River Valley and South China Sea Ecology and Environment Administration Ministry of Ecology and Environment National Meteorological Information Center China Meteorological Administration International Research Center of Big Data for Sustainable Development Goals Xiamen University Research Center for Climate and Atmosphere National Research and Innovation Agency (BRIN) Research Department European Centre for Medium-Range Weather Forecasts Department of Meteorology and Geophysics University of Vienna College of Meteorology and Oceanography National University of Defense Technology State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural Resources Stripe Inc. South San Francisco Ocean Scope CELAD

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