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2023 2nd International Conference on Aerospace and Control Engineering, ICoACE 2023

作者： Wei, Zhenyan Li, Jianfeng You, Weishuai Song, Shenmin Shi, Xiaoping Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Institute of Mechanical and Electrical Engineering Beijing100072 China School of Astronautics Harbin Institute of Technology No. 92 West Dazhi Street Nangang District Harbin150001 China

A novel SMC-based prescribed performance guidance law combined with a base generator (TBG) is proposed. A TBG-based modified Lyapunov function is first proposed, which ensures that the LOS tracking error converges into zero within a predefined time. A novel sliding manifold with adjusting convergent time property is proposed, which brings about a smaller control magnitude and predefined time convergent rate. To ensure a satisfied transit and steady performance, some converted variables are defined based on which a novel prescribed performance guidance law is constructed. The input saturation problem is properly solved by designing a novel TBG-based one-order auxiliary system. Extensive simulation results have verified the effectiveness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Lyapunov functions

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Experimental research on GM-APD LIDAR point cloud classification algorithm based on deep learning

Experimental research on GM-APD LIDAR point cloud classifica...

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2022 Applied Optics and Photonics China: Advanced Laser technology and Applications, AOPC 2022

作者： Jiang, Yanze Sun, Jianfeng Ding, Yuanxue Jiang, Peng Zhang, Hailong Li, Sining Zhou, Shuaijun National Key Laboratory of Science and Technology on Tunable Laser Institute of OptoElectronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (纸本)9781510662223

Geiger mode Avalanche Photo Diode (Gm-APD) array lidar is a lidar that can perform single-photon detection. It offers a wide range of applications due to its low power consumption, small size, and extended detecting distance. There haven't been many research on this detector's target classification because of its late development and small detector array. The classification technique based on the Gm-APD array lidar point cloud is the focus of this paper's research: Firstly, the Gm-APD array lidar is utilized to perform imaging tests on four targets from various angles in order to create a target classification *** that, several data preprocessing methods were chosen and implemented based on the characteristics of the obtained data, such as filling in missing values, performing range image and intensity image interpolation, using the principle of keyhole imaging to convert the range image to point cloud data, realizing the information fusion of distance image and intensity image, and using multiple point cloud data enhancement methods. Finally, the point cloud classification networks PointNet and PointNet++ are trained on point cloud data with varying levels of preprocessing, the results are compared and analyzed, and the impact of different preprocessing methods on the classification accuracy of the two networks is determined. Inferences were made and experiments were carried out to verify the inferences. The data set preprocessing method with the highest classification accuracy of the two networks is discovered, laying the groundwork for future Gm-APD lidar target classification and detection research. © 2023 SPIE.

关键词： Optical radar

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Design approach of contingency point return trajectory for manned lunar missions based on homotopy continuation 3

Design approach of contingency point return trajectory for m...

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2024 3rd International Conference on Aerospace, Aerodynamics and Mechatronics Engineering, AAME 2024

作者： Lu, Lin Li, Haiyang Dong, Tianshan Zhu, Binyu College of Aerospace Science and Engineering National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Intelligent Planning and Simulation for Aerospace Missions Changsha410073 China Beijing Institute of Spacecraft System Engineering Beijing100094 China

In terms of the requirement of contingency return during the circumlunar flight phase in manned lunar missions, this article presents a contingency point return trajectory design approach. In consideration of the point return constraint, an initial value estimate model is proposed. A nonlinear programming problem is constructed and solved by adopting an improved differential evolution algorithm with good global search ability. On the basis of the initial value estimate, homotopy continuation is used to gradually approximate and obtain the high-fidelity solution. The simulation results indicate that the design approach can effectively calculate a contingency point return trajectory with good convergence. © Published under licence by IOP Publishing Ltd.

关键词： Lunar missions

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Prediction of Hybrid Asynchronous Frequency Hopping Pattern based on Deep Learning in Wideband Spectrum

Prediction of Hybrid Asynchronous Frequency Hopping Pattern ...

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2023 China Automation Congress, CAC 2023

作者： Wang, Ya Wang, Jiaqi Yuan, Shuai Liu, Naijin Lu, Yuanming Qian Xuesen Laboratory of Space Technology China Academy of Space Technology Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Unit 63893 of Pla Luoyang China

ISBN: (纸本)9798350303759

In non-cooperative scenarios, wideband frequency hopping (FH) communication reconnaissance including FH signal detection, parameter estimation, and network sorting under single-channel reception is challenging. The FH pattern contains the most information about FH signals. So it is the core of FH parameter estimation. Based on the task analysis, this paper proposes a blind prediction framework combining deep learning (DL) and clustering methods to improve the accuracy and efficiency of FH pattern estimation for mixed signals in the wideband spectrum. The unique advantage of this framework is that it requires no prior signal information and anchors but exploits the inherent time-frequency (TF) properties of asynchronous FH signals. It has a strong generalization ability and can adapt to signals of any shape. Moreover, a new comprehensive evaluation metric, normalized root mean square error including missed detection (NRMSE-MD), suitable for sequence data prediction is proposed to evaluate the level of missed detection and false detection in signal monitoring. Experimental results demonstrate the superiority of the proposed framework and the effectiveness of the proposed evaluation metric. © 2023 IEEE.

关键词： Forecasting

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MTL-JER: Meta-Transfer Learning for Low-Resource Joint Entity and Relation Extraction

MTL-JER: Meta-Transfer Learning for Low-Resource Joint Entit...

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Neural Networks, Information and Communication Engineering (NNICE), International Conference on

作者： Da Peng Zhongmin Pei Delin Mo Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China Institute of War Studies Academy of Military Sciences

Joint entity and relation extraction has achieved impressive advances in NLP, such as document understanding and knowledge graph construction. The typical methods for entity and relation extraction typically break down the joint task into several smaller components or stages for ease of implementation, but this leads to a loss of the interconnected knowledge in the triple. Hence, we propose to model the triple in one module jointly. Furthermore, the labeling of a joint entity and relation extraction tasks is costly and domain-specific; therefore, it is important to improve its performance on low-resource data and domain adaption. To address this issue, we suggest using two sources that are rich in information, namely pre-trained models on large data and multi-domain text corpora. Pretraining allows us to provide the model with the fundamental ability to perform joint entity and relationship extraction. Second, through meta-learning on multi-domain text, we can improve the model's generalization capabilities, enabling it to perform well even with limited data. We present MTL-JER, a Meta-Transfer Learning method for Joint Entity and Relation Extraction in low-resource settings in this paper. Using exhaustive experiments on five datasets, we prove that our model obtains optimal results.

关键词： Adaptation models Training data Knowledge graphs Artificial neural networks Data models Data mining Labeling

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Trends and drivers of anthropogenic NOx emissions in China since 2020

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Environmental science and Ecotechnology 2024年第5期21卷 287-293页

作者： Hui Li Bo Zheng Yu Lei Didier Hauglustaine Cuihong Chen Xin Lin Yi Zhang Qiang Zhang Kebin He Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and EcologyTsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation and Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing 100041China Laboratoire des Sciences du Climat et de l’Environnement LSCE/IPSLCEA-CNRS-UVSQUniversite Paris-SaclayGif-sur-YvetteFrance Center for Satellite Application on Ecology and Environment Ministry of Ecology and Environment of ChinaBeijing 100094China Institute of Future Human Habitats Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Nitrogen oxides(NOx),significant contributors to air pollution and climate change,form aerosols and ozone in the ***,timely,and transparent information on NOx emissions is essential for decision-making to mitigate both haze and ozone ***,a comprehensive understanding of the trends and drivers behind anthropogenic NOx emissions from Chinadthe world's largest emitterdhas been lacking since 2020 due to delays in emissions *** we show a consistent decline in China's NOx emissions from 2020 to 2022,despite increased fossil fuel consumption,utilizing satellite observations as constraints for NOx emission estimates through atmospheric *** reduction is corroborated by data from two independent spaceborne instruments:the TROPOspheric Monitoring Instrument(TROPOMI)and the Ozone Monitoring Instrument(OMI).Notably,a reduction in transport emissions,largely due to the COVID-19 lockdowns,slightly decreased China's NOx emissions in *** subsequent years,2021 and 2022,reductions in NOx emissions were driven by the industry and transport sectors,influenced by stringent air pollution *** satellite-based inversion system developed in this study represents a significant advancement in the real-time monitoring of regional air pollution emissions from space.

关键词： China's NOx emissions Pollution control Socio-economic drivers Atmospheric inversion

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A study on finite false target jamming for radar track generation

A study on finite false target jamming for radar track gener...

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2023 International Conference on Electronic Information Engineering and Data Processing, EIEDP 2023

作者： Wang, Yanqi Wang, Chao Shi, Qingzhan Huang, Jingjian Yuan, Naichang College of Electronic Science and Technology National University of Defense Technology Changsha410073 China State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781510666160

To solve the problem that radar can still generate effective tracks to the covered target under the existing false target jamming technology, a method of jamming radar target track generation using finite false target signals is proposed through the plot and track correlation process of the radar in the initial stage of target searching and tracking. Through electronic reconnaissance, interception, and retransmission of radar signals by a jammer, a finite number of false target signals with random movement characteristics are generated around the covered target, interfering with track correlation during target data processing by radar. simulation examples demonstrate the effectiveness of the proposed method. © 2023 SPIE.

关键词： Data handling

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LEO Satellite Network Traffic Forecasting based on ARIMA-BPNN Model

LEO Satellite Network Traffic Forecasting based on ARIMA-BPN...

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Electronic Information Engineering and Computer Communication (EIECC), International Conference on

作者： Chi Han Wei Xiong Ronghuan Yu Jingyu Fu Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China Jiuquan Satellite Launch Center Jiuquan China

Satellite network traffic forecasting provides key information for routing and resource allocation, which is important for the efficient operation of satellite network. However, due to the self-similarity and long-range dependence (LRD) of satellite network traffic, traditional linear or non-linear network traffic forecasting models cannot achieve sufficient forecasting accuracy. A combined model of satellite network traffic forecasting based on BPNN and ARIMA is proposed. BPNN is adopted to forecast the residuals. EMD-ARIMA and BPNN forecasting results are combined to achieve satellite network traffic forecasting. Experimental results on the satellite network traffic data generated by the ON/OFF model show that forecast accuracy of the proposed method is better than traditional model, which verifies the effectiveness of the proposed satellite network traffic forecast model.

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Gearman Based Distributed Computation of Space Target Photometry

Gearman Based Distributed Computation of Space Target Photom...

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Informatics, Networking and Computing (ICINC), International Conference on

作者： Miao Tian Peixuan Li Wenbo Song Jieping Xu Science and Technology on Complex Electronic System Simulation laboratory Space Engineering University Beijing China

Photometry is an important optical characteristic of space targets. Due to the huge computational volume of the photometry of the full-angle of a space target, the computation time is long and is difficult to meet the realistic demand. In this study, a Gearman based distributed parallel computation framework is constructed to automatically decompose and distribute the photometry computation tasks, automatically balance the computational load, and compose the computational results. This method divides the target photometry calculation into four independent variables, conducts distributed parallel calculation respectively, and finally integrates the calculation results into single target photometry information. The distributed parallel photometry computation method based on Gearman framework is important for fast computation of full-angle photometry data of space targets and assisting space target situational awareness tasks.

关键词： Integrated optics Distributed databases Optical variables control Task analysis Informatics Photometry

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Multi-UAV Cooperative Path-planning Under complex Threat Environment

Multi-UAV Cooperative Path-planning Under Complex Threat Env...

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第42届中国控制会议

作者： Zhenchang Liu Yuting Liu Hongyin Zhao Hanchen Lu Mingrui Hao Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory

This paper proposes a cooperative path-planning method based on multi-Dubins path segments to meet the penetration requirements of UAVs in a complex threat environment. A pruning strategy is used in path-planning to sift path segments, and the diversity of threat avoidance paths is considered under a reasonable calculation amount. A threat intrusion strategy is designed for no safety path condition, which makes the cooperative path-planning method have excellent robustness. A cooperative path optimization method based on particle swarm optimization is adopted for the path length and collision avoidance *** simulation results show that the UAV cooperative paths can avoid the threat area under any starting and ending points, and path lengths are close to the expected length.

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