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Autonomous relative optical navigation based on unified modeling of external systematic errors

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Chinese Journal of Aeronautics 2024年第3期37卷 282-289页

作者： Dayi WANG Bowen SUN Maodeng LI Jiaxing LI Haiyin ZHOU Beijing institute of Spacecraft System engineering Beijing 100191China College of Sciences National University of Defense TechnologyChangsha 410073China national Key Laboratory of Space Intelligent Control Beijing Institute of Control EngineeringBeijing 100191China

To solve the problem that external systematic errors of the optical camera cannot be fully estimated due to limited computing resources,a unified dimensionality reduction representation method for the external systematic errors of the optical camera is proposed,and autonomous relative optical navigation is *** camera translational and misalignment errors are converted into a three-dimensional rotation error,whose differential model can be established through specific attitude control and appropriate ***,the rotation error and the relative motion state are jointly estimated in an augmented Kalman filter *** with the traditional method that estimates the camera translational and misalignment errors,the proposed method reduces the computational complexity in that the estimated state dimension is ***,as demonstrated by numerical simulation,the estimation accuracy is improved significantly.

关键词： Unified model Systematic errors Optical navigation Observability analysis Calibration

AstroPose:Astronaut pose estimation using a monocular camera during extravehicular activities

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Science China(Technological Sciences) 2024年第6期67卷 1933-1945页

作者： LIU ZiBin LI You WANG ChunHui LIU Liang GUAN BangLei SHANG Yang YU QiFeng College of Aerospace Science and engineering National University of Defense TechnologyChangsha410073China Key Laboratory of Human Factors engineering China Astronaut Research and Training CenterBeijing100094China

With the completion of the Chinese space station,an increasing number of extravehicular activities will be executed by astronauts,which is regarded as one of the most dangerous activities in human space *** guarantee the safety of astronauts and the successful accomplishment of missions,it is vital to determine the pose of astronauts during extravehicular *** article presents a monocular vision-based pose estimation method of astronauts during extravehicular activities,making full use of the available observation ***,the camera is calibrated using objects of known structures,such as the spacesuit backpack or the circular handrail outside the space ***,the pose estimation is performed utilizing the feature points on the *** proposed methods are validated both on synthetic and semi-physical simulation experiments,demonstrating the high precision of the camera calibration and pose *** further evaluate the performance of the methods in real-world scenarios,we utilize image sequences of Shenzhou-13 astronauts during extravehicular *** experiments validate that camera calibration and pose estimation can be accomplished solely with the existing observation resources,without requiring additional complicated *** motion parameters of astronauts lay the technological foundation for subsequent applications such as mechanical analysis,task planning,and ground training of astronauts.

关键词： monocular camera astronaut pose estimation camera calibration

Bionic Design and Experimental Validation of a Robotic Airship Inspired by the Physalia physalis

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Journal of Bionic engineering 2024年第2期21卷 740-753页

作者： Yueneng Yang Lili Chen Zhiyang Liu Shifeng Zhang College of Aerospace Science and engineering National University of Defense TechnologyNo.109Deya RoadKaiFu DistrictChangsha410073China Aerospace Technology institute China Aerodynamics Research and Development CenterMianyang621000China

The robotic airship is one of the most unique and promising green aircraft,however,as a“lighter-than-air aircraft”and“thermal aircraft”,its long-endurance flight has great difficulties in decreasing drag and controlling buoyancy and pressure under thermal *** this work,we reported a robotic airship inspired by the Physalia physalis,imitating its morphology,physiological structure,and biological *** hull is designed by imitating the morphology of the Physalia physalis,and the gasbags including a helium balloon,two ballonets,and a thermoregulation gasbag are designed by imitating the physiological structure and biological behaviors of the pneumatophore,bladder,and gland of the Physalia physalis,*** results show that the bionic airship has an increase of about 40%in lift-to-drag and decreases the pressure in helium balloon by 47.5%under thermal effects,and has better aerodynamic performances and thermoregulation performances than conventional airships.

关键词： Robotic airship Bionic design Aerodynamic performances Thermoregulation Physalia physalis

Ballistic target recognition based on multiple data representations and deep-learning algorithms

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Chinese Journal of Aeronautics 2024年第6期37卷 167-181页

作者： Lixun HAN Cunqian FENG Xiaowei HU Sisan HE Xuguang XU Air and Missile defense College Air Force Engineering UniversityXi’an 710051China College of Information and Communication National University of Defense TechnologyWuhan 430010China

Target recognition is a significant part of a Ballistic Missile defense System(BMDS).However,most existing ballistic target recognition methods overlook the impact of data representation on recognition *** paper focuses on systematically investigating the influences of three novel data representations in the Range-Doppler(RD)***,the Radar Cross Section(RCS)and micro-Doppler(m-D)characteristics of a cone-shaped ballistic target are ***,three different data representations are proposed:RD data,RD sequence tensor data,and RD trajectory *** accommodate various data inputs,deep-learning models are designed,including a two-Dimensional Residual Dense Network(2D RDN),a three-Dimensional Residual Dense Network-Gated Recurrent Unit(3D RDN-GRU),and a Dynamic Trajectory Recognition Network(DTRN).Finally,an Electromagnetic(EM)computation dataset is collected to verify the performances of the networks.A broad range of experimental results demonstrates the effectiveness of the proposed ***,several key parameters of the proposed networks and datasets are extensively studied in this research.

关键词： Ballistic target Micro-Doppler Deep learning Range-Doppler Radar target recognition

Color coded metadevices toward programmed terahertz switching

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Light(Science & Applications) 2024年第7期13卷 1383-1392页

作者： Weibao He Xiang’ai Cheng Siyang Hu Ziheng Ren Zhongyi Yu Shun Wan Yuze Hu Tian Jiang College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangshaChina. Nanhu Laser Laboratory National University of Defense TechnologyChangshaChina. Hunan Provincial Key Laboratory of High Energy Laser Technology National University of Defense TechnologyChangshaChina. institute for Quantum Science and Technology College of ScienceNational University of Defense TechnologyChangshaChina

Terahertz modulators play a critical role in high-speed wireless communication,non-destructive imaging,and so on,which have attracted a large amount of research ***,all-optical terahertz modulation,an ultrafast dynamical control approach,remains to be limited in terms of encoding and *** we experimentally demonstrated an optical-programmed terahertz switching realized by combining optical metasurfaces with the terahertz metasurface,resulting in 2-bit dual-channel terahertz *** terahertz metasurface,made up of semiconductor islands and artificial microstructures,enables effective all-optical programming by providing multiple frequency channels with ultrafast modulation at the nanosecond ***,optical metasurfaces covered in terahertz metasurface alter the spatial light field distribution to obtain color *** to the time-domain coupled mode theory analysis,the energy dissipation modes in terahertz metasurface can be independently controlled by color excitation,which explains the principle of 2-bit encoding *** work establishes a platform for all-optical programmed terahertz metadevices and may further advance the application of composite metasurface in terahertz manipulation.

关键词： terahertz surface excitation

Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： Rui Wang Zhiming Zhou Kaiwen Li Tao Zhang Ling Wang Xin Xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems engineering National University of Defense TechnologyChangsha 410073China the institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex *** the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

Security-Enhanced Directional Modulation Based on Two-Dimensional M-WFRFT

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China Communications 2024年第5期21卷 229-248页

作者： Zhou Zhuang Luo Junshan Wang Shilian Xia Guojiang School of Electronic Science National University of Defense TechnologyChangsha 410073China Beijing institute of Astronautical Systems engineering Beijing 100076China

Directional modulation(DM)is one of the most promising secure communication ***,when the eavesdropper is co-located with the legitimate receiver,the conventional DM has the disadvantages of weak anti-scanning capability,anti-deciphering capability,and low secrecy *** response to these problems,we propose a twodimensional multi-term weighted fractional Fourier transform aided DM scheme,in which the legitimate receiver and the transmitter use different transform terms and transform orders to encrypt and decrypt the confidential *** order to further lower the probability of being deciphered by an eavesdropper,we use the subblock partition method to convert the one-dimensional modulated signal vector into a twodimensional signal matrix,increasing the confusion of the useful *** results demonstrate that the proposed DM scheme not only provides stronger anti-deciphering and anti-scanning capabilities but also improves the secrecy rate performance of the system.

关键词： bit error rate directional modulation phased array secrecy rate weighted fractional Fourier transform

Preparation and characterization of Rb-doped TiO_(2) powders for photocatalytic applications

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Rare Metals 2024年第2期43卷 555-561页

作者： Lu Jia Li-Mei Yang Wei Wang Song-Tao Huang Zheng Xu national engineering Laboratory of Biohydrometallurgy General Research Institute for Nonferrous MetalsBeijing100088China

TiO_(2)nanoparticles doped with different concentrations of Rb were prepared by sol–gel *** crystal structures of samples were characterized by X-ray diffraction(XRD)and transmission electron microscopy(TEM).It was confirmed by the Rietveld refinement method that the as-prepared samples crystallize in anatase phase and Rb doping induces expansion and distortion of the crystal *** with the pure TiO_(2),the Rb-doped nanoparticles have smaller crystal size and better *** rate of methylene blue was used to evaluate the photocatalytic activity of Rb–TiO_(2).It indicated that doping Rb into TiO_(2)can effectively improve the photocatalytic activity of TiO_(2)and the mechanisms were discussed in *** using the sample doped with 0.20%Rb,methylene blue degraded with the fastest rate(97%within 60 min).

关键词： Rb doping TiO_(2) Photocatalysis Sol-gel

Physics-data coupling-driven method to predict the penetration depth into concrete targets

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Theoretical & Applied Mechanics Letters 2024年第3期14卷 184-192页

作者： Shuai Qin Hao Liu Jianhui Wang Qiang Zhao Lei Zhang institute of defense engineering AMSLuoyang 471000China Harbin engineering University Harbin 150001China

The projectile penetration process into concrete target is a nonlinear complex *** the increase ofexperiment data,the data-driven paradigm has exhibited a new feasible method to solve such complex ***,due to poor quality of experimental data,the traditional machine learning(ML)methods,whichare driven only by experimental data,have poor generalization capabilities and limited prediction ***,this study intends to exhibit a ML method fusing the prior knowledge with experiment *** newML method can constrain the fitting to experimental data,improve the generalization ability and the predic-tion *** results show that integrating domain prior knowledge can effectively improve theperformance of the prediction model for penetration depth into concrete targets.

关键词： Penetration into concrete Artificial neural networks Prior knowledge fusion Prediction model