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Radar automatic target recognition based on feature extraction for complex HRRP

Science in China(Series F) 2008年第8期51卷 1138-1153页

作者： du lan LIU HongWei BAO Zheng ZHANG JunYing National Laboratory of Radar Signal Processing Xidian University Xi'an 710071 China

Radar high-resolution range profile （HRRP） has received intensive attention from the radar automatic target recognition （RATR） community. Usually, since the initial phase of a complex HRRP is strongly sensitive to target position variation, which is referred to as the initial phase sensitivity in this paper, only the amplitude information in the complex HRRP, called the real HRRP in this paper, is used for RATR, whereas the phase information is discarded. However, the remaining phase information except for initial phases in the complex HRRP also contains valuable target discriminant information. This paper proposes a novel feature extraction method for the complex HRRP. The extracted complex feature vector, referred to as the complex feature vector with difference phases, contains the difference phase information between range cells but no initial phase information in the complex HRRR According to the scattering center model, the physical mechanism of the proposed complex feature vector is similar to that of the real HRRP, except for reserving some phase information independent of the initial phase in the complex HRRP. The recognition algorithms, frame-template establishment methods and preprocessing methods used in the real HRRP-based RATR can also be applied to the proposed complex feature vector-based RATR. Moreover, the components in the complex feature vector with difference phases approximate to follow Gaussian distribution, which make it simple to perform the statistical recognition by such complex feature vector. The recognition experiments based on measured data show that the proposed complex feature vector can obtain better recognition performance than the real HRRP if only the cell interval parameters are properly selected.

关键词： complex high-resolution range profile (HRRP) radar automatic target recognition (RATR) feature extraction minimum Euclidean distance classifier adaptive Gaussian classifier (AGC)

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Leveraging the Empirical Wavelet Transform in Combination with Convolutional LSTM Neural Networks to Enhance the Accuracy of Polar Motion Prediction

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Research in Astronomy and Astrophysics 2024年第9期24卷 214-224页

作者： Xu-Qiao Wang lan du Zhong-Kai Zhang Ze-Jun Liu Hao Xiang College of Geospatial Information Information Engineering UniversityZhengzhou 450001China Henan Industrial Technology Academy of Spatio-Temporal Big Data Zhengzhou 450046China

High-precision polar motion prediction is of great significance for deep space exploration and satellite *** motion is affected by a variety of excitation factors,and nonlinear prediction methods are more suitable for polar motion *** order to explore the effect of deep learning in polar motion *** paper proposes a combined model based on empirical wavelet transform(EWT),Convolutional Neural Networks(CNN)and Long Short Term Memory(LSTM).By training and forecasting EOP 20C04 data,the effectiveness of the algorithm is verified,and the performance of two forecasting strategies in deep learning for polar motion prediction is *** results indicate that recursive multi-step prediction performs better than direct multi-step prediction for short-term forecasts within 15 days,while direct multi-step prediction is more suitable for medium and long-term *** the 365 days forecast,the mean absolute error of EWT-CNN-LSTM in the X direction and Y direction is 18.25 mas and 15.78 mas,respectively,which is 23.5% and 16.2% higher than the accuracy of Bulletin *** results show that the algorithm has a good effect in medium and long term polar motion prediction.

关键词： data analysis methods:miscellaneous astrometry reference systems Earth

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Robust radar automatic target recognition algorithm based on HRRP signature

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Frontiers of Electrical and Electronic Engineering in China 2012年第1期7卷 49-55页

作者： Hongwei LIU Feng CHEN lan du Zheng BAO National Laboratory of Radar Signal Processing Xidian UniversityXi'an 710071China

Automatic target recognition （ATR） is an important function for modern radar. High resolution range profile （HRRP） of target contains target struc- ture signatures, such as target size, scatterer distribu- tion, etc, which is a promising signature for ATR. Sta- tistical modeling of target HRRPs is the key stage for HRRP statistical recognition, including model selection and parameter estimation. For statistical recognition al- gorithms, it is generally assumed that the test samples follow the same distribution model as that of the train- ing data. Since the signal-to-noise ratio （SNR） of the received HRRP is a function of target distance, the as- sumption may be not met in practice. In this paper, we present a robust method for HRRP statistical recogni- tion when SNR of test HRRP is lower than that of train- ing samples. The noise is assumed independent Gaus- sian distributed, while HRRP is modeled by probabilistic principal component analysis （PPCA） model. Simulated experiments based on measured data show the effective- ness of the proposed method.

关键词： radar target recognition high resolution range profile (HRRP) probabilistic principal component analysis (PPCA)

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Evaluating soil acidification risk and its effects on biodiversity–ecosystem multifunctionality relationships in the drylands of China

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Forest Ecosystems 2024年第2期11卷 162-171页

作者： lan du Shengchuan Tian Nan Zhao Bin Zhang Xiaohan Mu Lisong Tang Xinjun Zheng Yan Li State Key Laboratory of Desert and Oasis Ecology Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqi830011XinjiangChina University of Chinese Academy of Sciences Beijing100049China Fukang Station of Desert Ecology Chinese Academy of SciencesFukang831505XinjiangChina State Key Laboratory of Subtropical Silviculture Zhejiang A and F UniversityHangzhou311300ZhejiangChina

Background:Soil acidifcationn caused by anthropogenic activities may aft soil biochemical cydling,bidiversity,productivity,and multiple eosystem-related functions in ***,to date,such information is lacking to support this *** Based on a transect survey of 78 naturally assembled shrub communities,we caloulated acid deposition flux in Northwest China and evaluated its likely ecological ffets by testing three altemnative hypotheses,namely:.nidche complementarity,mass ratio,and vegetation quantity hypotheses Rao's quadratic entopy and community-weighted mean traits were employed to represent the complementary aspect of niche complementarity and mass ratio effects,***:We observed that in the past four decades,the concentrations of exchangeable base cations in soil in Northwest China have decreased significantly to the extent of having faced the risk of depletion,whereas changes in the calium carbonate content and pH of soil were not *** deposition primani ly increased the aboweground biomass and shrub density in shrublands but had no sigmificant effect on shrub richness and ecasystem multifunctionality(EMF),indicating that acid deposition had positive but weak ecological effects on dryland *** wd ghted mean of functional traits(representing the mass ratio hypothesis)correlated negatively with EMF,whereas both Rao's quadratic entropy(representing the niche complementarity hypothesis)and aboveground biomass(representing the vegetation quantity hypothesis)correlated positively but insignifcantly with *** biodiversity-EMF relationships highlight the fragility and instability of drylands relative to forest ***:The findings from this study serve as important reference points to understand the ris of soil acidification in arid regions and its impacts on biodiversity-EMF relationships.

关键词： Soil acidification risk Biodiversity Ecosystem multifunctionality Niche complementarity hypothesis Mass ratio hypothesis Vegetation quantity hypothesis

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Satellite Clock Offset Determination and Prediction with Integrating Regional Satellite‐ground and Inter‐satellite Data

Satellite Clock Offset Determination and Prediction with Int...

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第五届中国卫星导航学术年会

作者： Liu Li Shi Xin Tang Guifen du lan Zhu Lingfeng Guo Rui Beijing Satellite Navigation Center Information Engineering University

ISBN: (纸本)9783642547393

Time synchronization between Satellites is the foundation for satellite navigation system,which is realized by satellite‐ground clock offset determination and ***,satellite clock offset determination and prediction is a key technique for satellite navigation *** present,precise time synchronization between satellites by inter‐satellite link and auto‐time synchronization is considered to be important development direction for navigation domain.A satellite clock offset determination and prediction method by integrating regional satellite‐ground observation data and inter‐satellite observation data is *** first introduce some common used methods for satellite clock determination,and then discuss the principle and data process model for satellite clock determination based on inter‐satellite link *** provide the method of Helmert variance components estimation to determine and predict satellite clock based on integrating satellite‐ground and inter‐satellite observation *** last,we analysis the performance for our method by using real observation data and simulation data,the result shows the method overcomes the defects of regional monitoring network and improves the precise of prediction form 8ns to 1.5ns for MEO satellite when the satellites can’t been *** method also increases the satellite clock data when the satellites can be observed,which can improved the precise and reliability for determination and prediction satellite clock offset.

关键词： Navigation satellite Time synchronization Inter‐satellite link Clock offset determination Clock offset prediction.

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A new feature extraction method using the amplitude fluctuation property of target HRRP for radar automatic target recognition

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Frontiers of Electrical and Electronic Engineering in China 2006年第2期1卷 171-176页

作者： du lan LIU Hong-wei BAO Zheng ZHANG Jun-ying National Laboratory of Radar Signal Processing Xidian UniversityXi'anShaanxi 710071China

due to the aspect sensitivity of high-resolution range profile(HRRP),traditional radar HRRP target recognition methods usually use average profile within some target-aspect region as the target-aspect ***,the amplitude fluctuation property of target HRRP also represents some feature information of the *** on the scattering center model,a new feature extraction method using the amplitude fluctuation property of target HRRP is proposed in this *** weighted HRRP feature extracted by the new method can represent the scatterer distribution in every range cell,thereby it can describe the scattering property of the target *** experimental results based on measured data show that the new feature extraction method can greatly improve recognition performances.

关键词： Radar automatic target recognition(RATR) HRRP Feature extraction Scattering center model Average profile Variance profile

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China-ASEAN Cooperation Entering ‘Period of Maturity’

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China Report ASEAN 2018年第1期3卷 24-25页

作者： du lan Department of American Studies China Institute of International Studies

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Cordyceps cicadae extracts ameliorate renal malfunction in a remnant kidney model

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2011年第12期12卷 1024-1033页

作者： Rong ZHU Yi-ping CHEN Yue-yi DENG Rong ZHENG Yi-fei ZHONG Lin WANG lan-ping du Department of Nephrology Longhua Hospital Shanghai University of Traditional Chinese Medicine Shanghai 200032 China

Background and Objectives:Chronic kidney disease(CKD) is a growing public health problem with an urgent need for new pharmacological *** cicadae is widely used in traditional Chinese medicine(TCM) and has potential renoprotective *** current study aimed to determine any scientific evidence to support its clinical ***:We analyzed the potential of two kinds of *** extract,total extract(TE) and acetic ether extract(AE),in treating kidney disease simulated by a subtotal nephrectomy(SNx) ***-Dawley rats were divided randomly into seven groups:sham-operated group,vehicle-treated SNx,Cozaar,2 g/(kg·d) TE SNx,1 g/(kg·d) TE SNx,92 mg/(kg·d) AE SNx,and 46 mg/(kg·d) AE *** injury was monitored using urine and serum analyses,and hematoxylin and eosin(HE) and periodic acid-Schiff(PAS) stainings were used to analyze the level of *** expression of type IV collagen(Col IV),fibronectin(FN),transforming growth factor-β1(TGF-β1),and connective tissue growth factor(CTGF) was detected by ***:Renal injury,reflected in urine and serum analyses,and pathological changes induced by SNx were attenuated by TE and AE *** depositions of Col IV and FN were also decreased by the treatments and were accompanied by reduced expression of TGF-β1 and *** some respects,2 g/(kg·d) of TE produced better effects than ***:For the first time,we have shown that *** may inhibit renal fibrosis in vivo through the TGF-β1/CTGF ***,we conclude that the use of *** could provide a rational strategy for combating renal fibrosis.

关键词： Chronic kidney disease Cordyceps cicadae TGF-β Traditional Chinese medicine

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A Bridge to Friendship

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Beijing Review 2017年第42期60卷 36-37页

作者： du lan the China Institute of International Studies

The first China-U.S. Social and People- to-People Dialogue, co-chaired by Chinese Vice Premier Liu Yandong and U.S. Secretary of State Rex Tillerson, was successfully held in Washington, D.C. on September 28. With the theme of ＂＇living together for the next 50 years based on mu- tual understanding,＂ this dialogue provides a platform for China and the U.S. to exchange views on bilateral ties and cultural com- munication. At the dialogue, the two sides reached important consensus and issued the China-U.S. Social and Cultural Dialogue Action Plan.

关键词：国务院副总理社会文化对话华盛顿 COM 美国中国

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一种集成式Beta过程最大间隔一类分类方法

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电子与信息学报 2021年第5期43卷 1219-1227页

作者：张维杜兰西安电子科技大学雷达信号处理国家重点实验室西安710071

一类分类是一种将目标类样本和其他所有的非目标类样本区分开的分类方法。传统的一类分类方法针对所有训练样本建立一个分类器,忽视了数据的内在结构,在样本分布复杂时,其分类性能会严重下降。为了提升复杂分布情况下的分类性能,该文提... 详细信息

一类分类是一种将目标类样本和其他所有的非目标类样本区分开的分类方法。传统的一类分类方法针对所有训练样本建立一个分类器,忽视了数据的内在结构,在样本分布复杂时,其分类性能会严重下降。为了提升复杂分布情况下的分类性能,该文提出一种集成式Beta过程最大间隔一类方法。该方法利用Dirichlet过程混合模型(DPM)对训练样本聚类,同时在每一个聚类学习一个Beta过程最大间隔一类分类器。通过多个分类器的集成,可以构造出一个描述能力更强的分类器,提升复杂分布下的分类效果。DPM聚类模型和Beta过程最大间隔一类分类器在同一个贝叶斯框架下联合优化,保证了每一个聚类样本的可分性。此外,在Beta过程最大间隔一类分类器中,加入了服从Beta过程先验分布的特征选择因子,从而可以降低特征冗余度以及提升分类效果。基于仿真数据、公共数据集和实测SAR图像数据的实验结果证明了所提方法的有效性。

关键词：雷达信号处理一类分类 Dirichlet过程 Beta过程

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