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Chinese Journal of Aeronautics 2024年第9期37卷 463-474页

作者： Jianmin JI Jianhua REN Xunya JIANG Wei WANG Huilong YU Kai YIN Bo CHEN beijing institute of remote sensing equipment Beijing 100854China Shanghai Dong Jun Information and Technology Co.Ltd Shanghai 200050China

The electrical performance of radomes on high-speed aircraft can be influenced by the thermal and mechanical loads produced during high-speed flight,which can affect the detection dis-tance and accuracy of the guidance *** paper presents a new method that uses the Finite Difference Time Domain(FDTD)method to calculate the electrical performance of radomes under Thermo-Mechanical-Electrical(TME)*** method can accurately characterize the effects of material dielectric temperature drift and structural deformation on the electrical performance of the radome under flight conditions,enabling high-precision full-wave calculations of the broadband electrical performance of the *** method initiates by utilizing a Finite Element Grid Model(FE-GM)of the radome to sequentially acquire the radome's response temperature field and structural deformation field through thermal and mechanical ***,spatial mapping techniques are developed to accurately incorporate the dielectric temperature drift and structural deformation of the radome into its Yee grid Electromagnetic(EM)simulation model.A verification case was designed to test the proposed method,and the results confirmed its high computational ***,the effectiveness and necessity of the method were further demonstrated by analyzing the electrical performance of a fused silica ceramic radome used on a high-speed aircraft.

关键词： High-speed aircraft Radomes Thermo-Mechanical-Electrical(TME)coupling Finite Difference Time Domain(FDTD)method Spatial mapping

Behaviour recognition based on the integration of multigranular motion features in the Internet of Things

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Digital Communications and Networks 2024年第3期10卷 666-675页

作者： Lizong Zhang Yiming Wang Ke Yan Yi Su Nawaf Alharbe Shuxin Feng School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China beijing institute of remote sensing equipment Beijing100039China Applied College Taibah UniversityMedina42353Saudi Arabia

With the adoption of cutting-edge communication technologies such as 5G/6G systems and the extensive development of devices,crowdsensing systems in the Internet of Things(IoT)are now conducting complicated video analysis tasks such as behaviour *** applications have dramatically increased the diversity of IoT ***,behaviour recognition in videos usually requires a combinatorial analysis of the spatial information about objects and information about their dynamic actions in the temporal *** recognition may even rely more on the modeling of temporal information containing short-range and long-range motions,in contrast to computer vision tasks involving images that focus on understanding spatial ***,current solutions fail to jointly and comprehensively analyse short-range motions between adjacent frames and long-range temporal aggregations at large scales in *** this paper,we propose a novel behaviour recognition method based on the integration of multigranular(IMG)motion features,which can provide support for deploying video analysis in multimedia IoT crowdsensing *** particular,we achieve reliable motion information modeling by integrating a channel attention-based short-term motion feature enhancement module(CSEM)and a cascaded long-term motion feature integration module(CLIM).We evaluate our model on several action recognition benchmarks,such as HMDB51,Something-Something and *** experimental results demonstrate that our approach outperforms the previous state-of-the-art methods,which confirms its effective-ness and efficiency.

关键词： Behaviour recognition Motion features Attention mechanism Internet of things Crowdsensing

Nonlinear characteristics of torsional stiffness of a coilable mast with triangular section

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Chinese Journal of Aeronautics 2024年第10期37卷 313-324页

作者： Yu LIU Liang SUN Hai HUANG Shenyan CHEN Weipeng LI Xurui ZHAO School of Astronautics Beihang UniversityBeijing 100191China institute of remote sensing Satellite China Academy of Space TechnologyBeijing 100094China

With numerous applications coilable masts in high-precision astronomical observations,such as X-ray source observations,it is important to investigate mast *** date,there have been many studies on the bending stiffness of coilable masts,but few studies on their torsional stiffness,especially regarding the nonlinear characteristics of torsional stiffness of coilable masts under large torsional *** this paper,a nonlinear analysis method is presented to examine the torsional stiffness of coilable masts with triangular *** on the second-order bending buckling hypothesis of battens under large torsion deformation,the nonlinear relationship between torsional torque and torsional angle is obtained by analyzing torsional deformation and force of coilable *** method is used to analyze the torsional stiffness nonlinearity of a certain type of coilable mast which will be used in a practical application in the future and the results are verified by simulation and *** comparison results show that the error is within the acceptable range,which proves the effectiveness of the proposed method.

关键词： Coilable mast Torsion testing Torsional stiffness nonlinearity Torsional deformation Torsion simulation

Apatite Fission-Track Thermochronology in the Tamusu Area,Bayingobi Basin,NW China,and its Geological Significance

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Acta Geologica Sinica(English Edition) 2024年第3期98卷 585-601页

作者： TONG Qinlong QIN Mingkuan YE Fawang CNNC beijing Research institute of Uranium Geology National Key Laboratory of Remote Sensing Information and Image Analysis TechnologyBeijing 100029China

The Bayingobi basin is located in the middle of Central Asia Orogenic Belt,at the intersection of Paleo-Asian Ocean and Tethys Ocean,as well as the junction of multiple tectonic *** unique tectonic setting underpins the basin's intricate history of tectonic *** unravel the multifaceted tectono-thermal evolution within the southwestern region of the basin and to elucidate the implications of sandstone-hosted uranium mineralization,granitic and clastic rock samples were collected from the Zongnai *** and Yingejing depression,and apatite fission track(AFT)dating and thermal history simulation analysis were *** dating findings reveal that the apparent ages of all samples fall within the range of 244 Ma to 112 *** particular,the bedrock of the Zongnai *** Jurassic detrital apatite fission tracks have undergone complete annealing,capturing the uplift-cooling ***,the AFT ages of Cretaceous detrital rocks are either equivalent to or notably exceed the age of sedimentary strata,signifying the cooling age of the provenance.A comprehensive examination of AFT ages and palaeocurrent direction analyses suggests that the Cretaceous source in the Tamusu area predominantly originated from the central and southern sectors of the Zongnai ***,at a certain juncture during the Late Early Cretaceous,the Cretaceous provenance expanded to include the northern part of the Zongnai *** on the results of thermal history simulations and previous studies,it is considered that the Tamusu area has undergone four distinct tectonic uplift events since the Late *** first is the Late Permian to Early Triassic(260-240 Ma),which is associated with the closure of the Paleo-Asian Ocean and the accretionary orogeny within the Alxa *** second uplift event took place in the Early Jurassic(190-175 Ma)and corresponded to intraplate orogeny following the closure of the Paleo-Asian *** third uplift event is the Lat

关键词： apatite fission-track tectono-thermal history sandstone-hosted uranium deposit Bayingobi basin Central Asian Orogenic Belt

Long-term(2013-2022)mapping of winter wheat in the North China Plain using Landsat data:classification with optimal zoning strategy

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Big Earth Data 2024年第3期8卷 494-521页

作者： Yifei Liu Xuehong Chen Jin Chen Yunze Zang Jingyi Wang Miao Lu Liang Sun Qi Dong Bingwen Qiu Xiufang Zhu State Key Laboratory of remote sensing Science Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijingChina beijing Engineering Research Center for Global Land remote sensing Products Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijingChina State Key Laboratory of Crop Gene Resources and Breeding Institute of Crop SciencesChinese Academy of Agricultural Sciences(CAAS)BeijingChina State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijingChina Key Laboratory of Spatial Data Mining&Information Sharing of Ministry of Education Academy of Digital China(Fujian)Fuzhou UniversityFuzhouChina

security and formulating agricultural *** data are the only available source for long-term winter wheat mapping in the North China Plain due to the fragmented landscape in this *** various methods,such as index-based methods,curve similarity-based methods and machine learning-based methods,have been developed for winter wheat mapping based on remote sensing,the former two often require satellite data with high temporal resolution,which are unsuitable for Landsat data with sparse *** learning is an effective method for crop classification using Landsat ***,applying machine learn-ing for winter wheat mapping in the North China Plain encounters two main issues:1)the lack of adequate and accurate samples for classifier training;and 2)the difficulty of training a single classifier to accomplish the large-scale crop mapping due to the high spatial heterogeneity in this *** address these two issues,we first designed a sample selection rule to build a large sample set based on several existing crop maps derived from recent Sentinel data,with specific consideration of the confusion error between winter wheat and winter rapeseed in the available crop ***,we developed an optimal zoning method based on the quadtree region splitting algorithm with classification feature consistency criterion,which divided the study area into six subzones with uni-form classification *** each subzone,a specific random forest classifier was trained and used to generate annual winter wheat maps from 2013 to 2022 using Landsat 8 OLI *** sample validation confirmed the high accuracy of the produced maps,with an average overall accuracy of 91.1%and an average kappa coefficient of 0.810 across different *** derived winter wheat area also has a good correlation(R2=0.949)with census area at the provincial *** results underscore the reliability of the produced annual winter wheat *** experiments demonstrate that

关键词： Winter wheat mapping Landsat machine learning North China Plain optimal zoning

Toward Establishing a Low-cost UAV Coordinated Carbon Observation Network(LUCCN):First Integrated Campaign in China

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Advances in Atmospheric Sciences 2024年第1期41卷 1-7页

作者： Dongxu YANG Tonghui ZHAO Lu YAO Dong GUO Meng FAN Xiaoyu REN Mingge LI Kai WU Jing WANG Zhaonan CAI Sisi WANG Jiaxu GUO Liangfu CHEN Yi LIU Carbon Neutrality Research Center(CNRC) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Middle Atmospheric Physics and Global Environment Observation(LAGEO) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of remote sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China National remote sensing Center of China Beijing 100036China The Administrative Center for China’s Agenda 21 Beijing 100862China

In this study,we introduce our newly developed measurement-fed-perception self-adaption Low-cost UAV Coordinated Carbon Observation Network(LUCCN)*** LUCCN primarily consists of two categories of instruments,including ground-based and UAV-based in-situ *** use the GMP343,a low-cost non-dispersive infrared sensor,in both ground-based and UAV-based *** first integrated measurement campaign took place in Shenzhen,China,4 May *** the campaign,we found that LUCCN’s UAV component presented significant data-collecting advantages over its ground-based counterpart owing to the relatively high altitudes of the point emission sources,which was especially obvious at a gas power plant in *** emission flux was calculated by a crosssectional flux(CSF)method,the results of which differed from the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC).The CSF result was slightly larger than others because of the low sampling rate of the whole emission cross *** LUCCN system will be applied in future carbon monitoring campaigns to increase the spatiotemporal coverage of carbon emission information,especially in scenarios involving the detection of smaller-scale,rapidly varying sources and sinks.

关键词： CO_(2) measurement networks power station carbon emission cross-sectional flux method

Spatial-temporal variations of surface water area during 1986-2018 in Qinghai Province,northwestern China based on Google Earth Engine

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Big Earth Data 2024年第2期8卷 333-349页

作者： Luying Zhu Haifeng Tian Ni Huang Li Wang Zheng Niu State Key Laboratory of remote sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina College of Resources and Environment University of Chinese Academy of SciencesBeijingChina College of Geography and Environmental Science Henan UniversityKaifengChina

Called the“Water Tower”,the water resource in Qinghai Province plays a vital role in the ecological environment of northwestern ***,significant uncertainty exists regarding its spatialtemporal *** this study,the data on the surface water of Qinghai Province from 1986 to 2018 was extracted and a systemic analysis of its spatial-temporal variations and responses to climate change was conducted using the Google Earth Engine(GEE)cloud processing *** findings revealed that the surface water in Qinghai Province was primarily concentrated in the Qaidam Basin,the Hoh Xil Nature Reserve,and Qinghai *** surface water area in Qinghai Province exhibited an overall increasing trend,with the temperature and precipitation being the primary drivers of this *** results provide crucial insights into the variations of surface water variations in Qinghai Province,northwestern China,under the influence of climate change.

关键词： Qinghai Province Google Earth Engine surface water climate change

RGB-guided hyperspectral image super-resolution with deep progressive learning

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 679-694页

作者： Tao Zhang Ying Fu Liwei Huang Siyuan Li Shaodi You Chenggang Yan School of Computer Science and Technology Beijing Institute of TechnologyBeijingChina Satellite Information Intelligent Processing and Application Research Laboratory Beijing Institute of Remote SensingBeijingChina Key Laboratory of Spectral Imaging Technology Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of SciencesXi'anChina institute of Informatics University of AmsterdamAmsterdamNetherlands School of Communication Engineering Hangzhou Dianzi UniversityHangzhouChina

Due to hardware limitations,existing hyperspectral(HS)camera often suffer from low spatial/temporal ***,it has been prevalent to super-resolve a low reso-lution(LR)HS image into a high resolution(HR)HS image with a HR RGB(or mul-tispectral)image *** approaches for this guided super-resolution task often model the intrinsic characteristic of the desired HR HS image using hand-crafted ***,researchers pay more attention to deep learning methods with direct supervised or unsupervised learning,which exploit deep prior only from training dataset or testing *** this article,an efficient convolutional neural network-based method is presented to progressively super-resolve HS image with RGB image ***-ically,a progressive HS image super-resolution network is proposed,which progressively super-resolve the LR HS image with pixel shuffled HR RGB image ***,the super-resolution network is progressively trained with supervised pre-training and un-supervised adaption,where supervised pre-training learns the general prior on training data and unsupervised adaptation generalises the general prior to specific prior for variant testing *** proposed method can effectively exploit prior from training dataset and testing HS and RGB images with spectral-spatial *** has a good general-isation capability,especially for blind HS image *** experimental results show that the proposed deep progressive learning method out-performs the existing state-of-the-art methods for HS image super-resolution in non-blind and blind cases.

关键词： computer vision deep neural networks image processing image resolution unsupervised learning

A review on the developments and space applications of mid- and long-wavelength infrared detection technologies

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Frontiers of Information Technology & Electronic Engineering 2024年第8期25卷 1031-1056页

作者： Yuying WANG Jindong LI Hezhi SUN Xiang LI beijing institute of Spacecraft System Engineering China Academy of Space TechnologyBejing 100094China institute of remote sensing Satellite China Academy of Space TechnologyBeijing 100094China

Mid-wavelength infrared(MWIR)detection and long-wavelength infrared(LWIR)detection constitute the key technologies for space-based Earth observation and astronomical *** advanced ability of infrared(IR)detection technology to penetrate the atmosphere and identify the camouflaged targets makes it excellent for space-based remote ***,such detectors play an essential role in detecting and tracking low-temperature and far-distance moving ***,due to the diverse scenarios in which space-based IR detection systems are built,the key parameters of IR technologies are subject to unique *** review the developments and features of MWIR and LWIR detectors with a particular focus on their applications in space-based *** conduct a comprehensive analysis of key performance indicators for IR detection systems,including the ground sampling distance(GSD),operation range,and noise equivalent temperature difference(NETD)among others,and their interconnections with IR detector ***,the influences of pixel distance,focal plane array size,and operation temperature of space-based IR remote sensing are *** development requirements and technical challenges of MWIR and LWIR detection systems are also identified to achieve high-quality space-based observation platforms.

关键词： Infrared detection Space application Mid-and long-wavelength infrared detection Space-based Earth observation remote sensing

Precise orbit determination for Tianwen-1 during mapping phase

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Astrodynamics 2024年第3期8卷 471-481页

作者： Shanhong Liu Jing Kong Jianfeng Cao Hao Huang Haijun Man Jianguo Yan Xie Li National Key Laboratory of Science and Technology on Aerospace Flight Dynamics Beijing100094China beijing Aerospace Control Center Beijing100094China institute for Frontiers in Astronomy and Astrophysics Bejing Normal UniversityBeijing100875China Astronomy Department Bejing Normal UniversityBeijing100875China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan430079China

The mapping phase is a key stage of the Tianwen-1 orbiter. It has the longest exploration time and gathers abundant radio tracking data via the Chinese deep space network. Thus, it also provides opportunities for radio science research topics such as the Mars gravity field model, ephemeris, and radio occultation experiments. At this stage, the need for imaging takes the highest priority, leading to frequent attitude adjustments for the spacecraft, which presents challenges for Precise Orbit Determination (POD). To improve the accuracy of the spacecraft’s orbit, this study analyzes the effects of arc length, the empirical acceleration, and the solar radiation pressure parameters on POD, considering the limited number of radio tracking observations. For one-day arcs, the POD is not able to adequately account for wheel off-loading and a few unknown forces with limited observations, but reasonable fitting is performed for the wheel off-loading occurring during tracking periods or the gap between two tracking periods. When extending the POD arc to three days, the estimated empirical acceleration can be well-fitted and reflects the aggregation feature, but the solar radiation pressure parameter has little impact on POD results. The root mean square of two-way range-rate residuals after POD is about 0.18-0.35 mm/s;the orbital position accuracy of 60% of the arcs is better than 100 m.

关键词： empirical acceleration mapping phase precise orbit determination(POD) radio science