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Computer Communication and Artificial Intelligence (CCAI), International Conference on

作者： Jing Cao Xiaoqin Xue Guojiang Xia Beijing Institute of Aerospace Systems Engineering Beijing China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing China

ISBN: (数字)9798350362763

ISBN: (纸本)9798350362770

UAV formation networks are widely used in military and civilian industries due to their high flexibility and scalability, however, due to the complex space environment in which UAV formations are located, they are susceptible to different types of interference such as climate and radiation, resulting in changes in service transmission performance. Therefore, in order to evaluate the impact of interference on the performance of UAV formation network, this paper first constructs a UAV formation network model, then defines a series of index parameters to measure network performance from the perspective of network structure and network business, and conducts simulation experiments for the network spatial structure and performance of different user QoS (Quality of Service), and finally carries out theoretical analysis and simulation evaluation of the performance changes of the network before and after different types of interference. It provides a reference for the design and application of UAV formation network.

关键词： Industries Analytical models Scalability Computational modeling Interference Quality of service Autonomous aerial vehicles

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Influences of the NAO on the North Atlantic CO2 Fluxes in Winter and Summer on the Interannual Scale

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Advances in Atmospheric sciences 2019年第11期36卷 1288-1298页

作者： Yujie JING Yangchun LI Yongfu XU Guangzhou FAN State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China School of Atmospheric Sciences Chengdu University of Information Technology Chengdu 610225 China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and Technology Qingdao 266237 China Department of Atmospheric Chemistry and Environmental Sciences College of Earth Science University of Chinese Academy of Sciences Beijing 100049 China

The differences in the influences of the North Atlantic Oscillation (NAO) on the air–sea CO2 fluxes (fCO2) in the North Atlantic (NA) between different seasons and between different regions are rarely fully investigated. We used observation-based data of fCO2, surface-ocean CO2 partial pressure (pCO2sea), wind speed and sea surface temperature (SST) to analyze the relationship between the NAO and fCO2 of the subtropical and subpolar NA in winter and summer on the interannual time scale. Based on power spectrum estimation, there are significant interannual signs with a 2–6 year cycle in the NAO indexes and area-averaged fCO2 anomalies in winter and summer from 1980 to 2015. Regression analysis with the 2–6 year filtered data shows that on the interannual scale the response of the fCO2 anomalies to the NAO has an obvious meridional wave-train-like pattern in winter, but a zonal distribution in summer. This seasonal difference is because in winter the fCO2 anomalies are mainly controlled by the NAO-driven wind speed anomalies, which have a meridional distribution pattern, while in summer they are dominated by the NAO-driven SST anomalies, which show distinct zonal difference in the subtropical NA. In addition, in the same season, there are different factors controlling the variation of pCO2sea in different regions. In summer, SST is important to the interannual variation of pCO2sea in the subtropical NA, while some biogeochemical variables probably control the pCO2sea variation in the subpolar NA.

关键词： air-sea CO2 flux North Atlantic Oscillation interannual time scale wind speed surface-ocean CO2 partial pressure

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Regional Meteorological Patterns for Heavy Pollution Events in Beijing

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Journal of Meteorological Research 2017年第3期31卷 597-611页

作者： ting you renguang wu gang huang guangzhou fan college of atmospheric sciences chengdu university of information technologyChengdu 610225 center for monsoon system research institute of atmospheric physicschinese academy of sciencesBeijing 100029 state key laboratory of numerical modeling for atmospheric sciences and geophysical fluid dynamics institute of atmospheric physicschinese academy of sciencesBeijing 100029 laboratory for regional oceanography and numerical modeling qingdao national laboratory for marine science and technologyQingdao 266237 joint center for global change studies Beijing100875 university of chinese academy of sciences Beijing 100049

The present study investigates meteorological conditions for the day-to-day changes of particulate matter （PM） concentration in Beijing city during the period 2008-2015. The local relationship of PM concentration to surface air temperature, pressure, wind speed, and relative humidity displays seasonal changes and year-to-year variations. The average correlation coefficient with PMI0 in spring, summer, fall, and winter is 0.45, 0.40, 0.38, and 0.30 for air tem- perature; -0.45, -0.05, -0.40, and -0.45 for pressure; 0.13, 0.04, 0.53, and 0.50 for relative humidity; and -0.18, -0.11, -0.45, and -0.33 for wind speed. A higher correlation with wind speed is obtained when wind speed leads by halfa day. The heavily polluted and clean days, which are defined as the top and bottom 10% of the PM values, show obvious differences in the regional distribution of air temperature, pressure, and wind. Polluted days correspond to higher air temperature in all the four seasons, lower sea level pressure and anomalous southerly winds to the south and east of Beijing in spring, fall, and winter, and a northwest-southeast contrast in the pressure anomaly and anom- alous southerly winds in summer. Higher relative humidity is observed on polluted days in fall and winter. The pol- luted days are preceded by an anomalous cyclone moving from the northwest, accompanied by lower pressure and higher air temperature, in all four seasons. This feature indicates the impacts of moving weather systems on local meteorological conditions for day-to-day air quality changes in Beijing.

关键词： PM10 Beijing local meteorology seasonal dependence weather system

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Ballistic Target Micro-motion Parameters Identification with CNN Denoiser Based on Deep Learning

Ballistic Target Micro-motion Parameters Identification with...

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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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Climate-Vegetation Interannual Variability in a Coupled Atmosphere-Ocean-Land Model

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Advances in Atmospheric sciences 2009年第3期26卷 599-612页

作者：智海王盘兴丹利俞永强徐永福郑伟鹏 Nanjing University of Information Science and Technology Nanjing 210044 The National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 START Regional Center for Temperate East Asia and Key Laboratory of Regional Climate-Environmentfor Temperate East Asia Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029 The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029

The coupled models of both the Global Ocean-Atmosphere-Land System （GOALS） and the Atmosphere- Vegetation Interaction Model （GOALS-AVIM） are used to study the main characteristics of interannual variations. The simulated results are also used to investigate some significant interannual variability and correlation analysis of the atmospheric circulation and terrestrial ecosystem. By comparing the simulations of the climate model GOALS-AVIM and GOALS, it is known that the simulated results of the interannual variations of the spatial and temporal distributions of the surface air temperatures and precipitation are generally improved by using AVIM in GOALS-AVIM. The interannual variation displays some distinct characteristics of the geographical distribution. Both the Net Primary Production （NPP） and the Leap Area Index （LAI） have quasi 1-2-year cycles. Meanwhile, precipitation and the surface temperatures have 2-4- year cycles. Conditions when the spectrum density values of GOALS are less than those of GOALS-AVIM, tell us that the model coupled with AVIM enhances the simulative capability for interannual variability and makes the annual cycle variability more apparent. Using Singular Value Decomposition （SVD） analysis, the relationship between the ecosystem and the atmospheric circulation in East Asia is explored. The result shows that the strengthening and weakening of the East Asian monsoon, characterized by the geopotential heights at 500 hPa and the wind fields at 850 hPa, correspond to the spatiotemporal pattern of the NPP. The correlation between NPP and the air temperature, precipitation and solar radiation are different in interannual variability because of the variation in vegetation types.

关键词： interannual variability net primary production atmosphere-vegetation interaction model twoway interaction

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A Novel Deceptive Jamming Method Via Frequency Diverse Array

A Novel Deceptive Jamming Method Via Frequency Diverse Array

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Wei Mao Hui Wang Shunsheng Zhang Xiangrong Liu National Key Laboratory of Science and Technology Test Physics and Numerical Mathematics Beijing China Research Institute of Electronic Science and Technology University of Electronic Science and Technology of China Chengdu China

Different from traditional single-element and phased-array antennas, frequency diverse array (FDA) uses a slight frequency offset across the elements to produce angle-, range- and even time-dependent transmit beampattern, which provides promising potentials to develop new jamming techniques on synthetic aperture radar (SAR) imaging. In this paper, we propose a novel deception jamming method against SAR imaging, which uses FDA to quickly generate false targets. Moreover, the position of the false target is controlled by the jammer, and the number of false targets is determined by the number of FDA elements. The proposed methods are validated by extensive simulation results with range-Doppler imaging algorithm.

关键词： Jamming Synthetic aperture radar Imaging Azimuth Interference Radar imaging

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Composite data fusion algorithm for miniature vehicles building navigation base in formation flying

Composite data fusion algorithm for miniature vehicles build...

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IEEE Workshop on Signal Processing Systems (SIPS)

作者： Runle Du Jiaqi Liu Zhifeng Li Zhenhong Niu Zhiye Jiang Yadong Yang National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China (100076) China Academy of Launch Vehicle Technology Beijing China (100076)

When multiple miniature vehicles with individual position and inter-vehicle distance measurement ability collaborate in a formation, navigation base can be established by data fusion in a decentralized and standalone scheme. A Composite Data Fusion (CDF) algorithm which combines Least Square Error and Kalman Filtering is proposed in this paper to build navigation base with optimized computing stress. In CDF, Enhanced LSE is incorporated as the preprocessing stage to build a coarse estimation and handle temporary or permanent group number failure. KF stage is then built to further alleviate noises in the pre-processed estimations In CDF, the dynamic model can be much simpler than KF, so the computation load is reduced while the result still has the advantage of high precision. Simulation results show that, when the fault rate of measurement in each vehicle goes 5 thousandth, the result is still acceptable. The computation time of the proposed method is less than three percent of that of KF, while its precision is almost the same to that of KF.

关键词： Vehicles Kalman filters Navigation Mathematical model Equations Data integration

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Dual-band checkerboard plasma electromagnetic surface for radar cross section reduction

Dual-band checkerboard plasma electromagnetic surface for ra...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Qiang Xu Zhifeng Li Jinjun Mo National University of Defense Technology Changsha China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematical Beijing China

ISBN: (纸本)9781538616093

Radar cross section (RCS) can be reduced along the principal planes by applying electromagnetic band gap (EBG) structures. Checkerboard plasma electromagnetic surface (PES), combining with EBG and plasma layer, can realize a narrow band near 3 GHz and a wide band 10-dB radar cross section reduction (RCSR) covered X-band, by redirecting the scattered fields towards four quadrants. Bistatic RCS of the checkerboard PES is simulated and the results compared to the corresponding perfect electric conductor (PEC) surface show that the maxima of the bistatic RCS pattern are reduced by 5.4 dB at fixed frequency 10 GHz.

关键词： Plasmas Periodic structures Metamaterials Electromagnetics Radar cross-sections Electromagnetic scattering

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Differences in Meteorological Conditions between Days with Persistent and Non-Persistent Pollution in Beijing, China

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Journal of Meteorological Research 2018年第1期32卷 81-98页

作者： Ting YOU Renguang WU Gang HUANG Center for Monsoon System Research Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 College of Atmospheric Sciences Chengdu University of Information Technology Chengdu 610225 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and Technology Qingdao 266237 Joint Center for Global Change Studies Beijing 100875 University of Chinese Academy of Sciences Beijing 100049

We compared the regional synoptic patterns and local meteorological conditions during persistent and non-persistent pollution events in Beijing using US NCEP–Department of Energy reanalysis outputs and observations from meteorological stations. The analysis focused on the impacts of high-frequency（period 〈 90 days） variations in meteorological conditions on persistent pollution events（those lasting for at least 3 days）. Persistent pollution events tended to occur in association with slow-moving weather systems producing stagnant weather conditions, whereas rapidly moving weather systems caused a dramatic change in the local weather conditions so that the pollution event was short-lived. Although Beijing was under the influence of anomalous southerly winds in all four seasons during pollution events, notable differences were identified in the regional patterns of sea-level pressure and local anomalies in relative humidity among persistent pollution events in different seasons. A region of lower pressure was present to the north of Beijing in spring, fall, and winter, whereas regions of lower and higher pressures were observed northwest and southeast of Beijing, respectively, in summer. The relative humidity near Beijing was higher in fall and winter, but lower in spring and summer. These differences may explain the seasonal dependence of the relationship between air pollution and the local meteorological variables. Our analysis showed that the temperature inversion in the lower troposphere played an important part in the occurrence of air pollution under stagnant weather *** results from this study are based on a limited number of events and thus require validation using more data.

关键词： persistent and non-persistent pollution events regional synoptic patterns local meteorological conditions temperature inversion stability index Beijing

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Plasma Diagnosis Method Based on Microwave Reflection Characteristics By GA-ANN

Plasma Diagnosis Method Based on Microwave Reflection Charac...

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International Conference on Microwave and Millimeter Wave technology Proceedings

作者： Yu-hang Shi Run-hui Wu Jin-jun Mo School of Information And Communication Guilin University of Electronic Technology Guilin China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing China

ISBN: (数字)9798350389968

ISBN: (纸本)9798350389975

In this paper, a microwave reflection method based on fusion algorithm is proposed to diagnose the peculiarity of plasma. This fusion algorithm is composed of genetic algorithm (GA) and neural network (ANN), that is GA-ANN. Only a single horn antenna is used to emit spherical waves to the preset plasma, and the scattering peculiarity of the horn antenna (impedance bandwidth, resonance point and gain) and the corresponding plasma characteristics (characteristic frequency, collision frequency) are obtained. The weight and bias of ANN are optimized by GA screening mechanism. Then GA-ANN is used to establish the mapping relationship between the scattering characteristics of antenna and plasma, which is finally used to diagnose the unknown plasma characteristics. The experimental results show that the relative error of plasma diagnosis using GA-ANN is 0.7 lower than that using ANN alone.

关键词： Microwave antennas Microwave integrated circuits Horn antennas Scattering Resonant frequency Reflection Resonance

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