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Multi-Targets Visiting Orbit Design Based on Numerical Method

Guidance,Navigation and Control 2025年第1期05卷 139-148页

作者： Zenan Zhong Zhengxiang Sun Songyan Wang Tao Chao Ming Yang Control and Simulation Center Harbin Institute of Technology National Key Laboratory of Modeling and Simulation for Complex Systems Harbin Institute of Technology Beijing Institute of Space Long March Vehicle

In this paper, for the two/three targets in the circle orbit with the same altitude, a numerical method is presented to design an orbit for a spacecraft to visit multiple targets without maneuvering. First,for the two targets' case, an equation is established by the relationship of the two angles that both are the function of the time, one of the angles is the angle between two targets' geocentric position vectors at two times, and another one is the spacecraft flight angle during the two times. The visit time can be solved by the assumption that one of the visit times is known in the equation, and the orbit element can be transferred from the position and velocity vector determined by the solved visit time. Then, for the three targets' case, the problem is decoupled into two cases of two targets, and there is a public target in each case. Based on the method for two targets, two different orbits can be obtained by determining the visit time of the public target. The difference between two orbits can be expressed by the difference in velocity vectors of the public target at different times. A sampling method is utilized to select two velocity vectors with relatively small differences as initial values, the Newton iteration method is used to obtain visit times with higher accuracy. simulation results illustrate the effectiveness of the orbit design methods.

关键词： Orbit design method multiple targets visit circle orbit non-maneuvering

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Optimal Deployment of Target Localization With Distance-Dependent Noise

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IEEE Internet of Things Journal 2025年

作者： Tian, Junxi Yang, Ming Chao, Tao Harbin Institute of Technology Control and Simulation Center National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150001 China

The cooperative localization of radio-based distance measurement is one of the methods to effectively suppress the nonline of sight (NLOS) ranging errors and as a complement to visual/global navigation satellite system (GNSS) localization for unmanned aerial vehicle (UAV) in GNSS challenging or denied environments due to its motility. Target localization can be regarded as a special case of cooperative localization. Meanwhile, the UAV can be considered as a ranging node when the ranging terminal is rigidly mounted on the UAV. To improve the target localization accuracy, the optimal deployment of anchor UAVs is one of the factors we consider when the noise characteristics are different. In this paper, the range-dependent noise in a real flight environment is considered and modeled separately according to the difference in noise characteristics. Subsequently, based on this correlation model, the Fisher information matrix (FIM) and a cost function derived from the A-optimal criterion are provided. Finally, the optimal deployment conditions and the minimum mean square error (MMSE) can be derived by minimizing the cost function as the objective. Through simulation and localization experiments, the validity of the optimal deployment conditions and the corresponding MMSE are verified. Meanwhile, it is concluded that when the noise is range-dependent, it will not affect the optimal deployment result but will significantly change the value of MMSE. © 2014 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Dynamic-Aware and Static Context Network for large-scale 3D place recognition

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Knowledge-Based systems 2025年 319卷

作者： Liao, Ming Di, Xiaoguang Liu, Maozhen Lv, Teng Zhang, Xiaofei Zhu, Runwen Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China

3D point cloud-based place recognition enables robots to obtain precise global positions without GPS, correct trajectory drift in SLAM, and recover from the kidnapped robot problem. However, in outdoor environments, the presence of moving objects can cause occlusions in point clouds and introduce noise into the data, leading to localization failures. To address this issue, we propose a Dynamic-Aware and Static Context Network (DASC-Net) for large-scale 3D place recognition. Our approach leverages the spatio-temporal consistency of point cloud sequences to accurately segment dynamic objects while incorporating static point cloud context to compensate for feature loss caused by noise interference or occlusions from dynamic objects, thereby enhancing robustness and generalization. Specifically, DASC-Net adopts a two-stage strategy: first, it introduces a coarse-to-fine moving object segmentation method to effectively eliminate dynamic noise;second, it utilizes spatial context association and multi-scale feature aggregation to improve static feature representation and matching. Extensive experimental results demonstrate that DASC-Net outperforms existing place recognition approaches, particularly in dynamic scenes. © 2025

关键词： Image segmentation

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Design of large ring-column antenna satellite attitude-orbit integrated füll propulsion system

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Zhendong yu Chongji/Journal of Vibration and Shock 2025年第11期44卷 1-11页

作者： Wang, Shijie Sun, Minzhe Gao, Feng Ji, Yi Sun, Guanghui Dong, Fuxiang School of Astronautics Harbin Institute of Technology Harbin150001 China Frontier Science Center of Space Environment and Interaction of Matters Harbin150001 China State Key Lab for Modeling and Simulation of Complex Systems Harbin150001 China General Department of Communication and Navigation Satellite China Academy of Space Technology Beijing100094 China

As a key space structure in geostationary orbit, 100-meter level large ring-column antenna satellite is tasked with providing high-speed information transmission and stable communication Service in this orbit. This requires satellites having precise orbit maintenance and attitude control capabilities. Due to such satellites typically having larger masses and special structural designs, here, the high-precision orbit prediction algorithm was used to finely model and analyze effects of key space environmental factors of solar pressure, non-spherical perturbations and 3-body gravity on space Operation of such spacecrafts. Furthermore, referring to the design concept of formation-flying gravity field measurement satellites, a distributed füll thrust control strategy based on thruster layout optimization for such spacecrafts was proposed. Then, an improved explicit model predictive control algorithm was proposed based on Laguerre function to convert device capability limitations and Performance requirements into input-output constraints, combine multi-parameter programming, and realize attitude-orbit integrated control of such satellites. The simulation results showed that during stable Operation, position maintenance errors of such satellites can be controlled within a meter-level ränge, and attitude angle errors are better than 0. 03°;the computational efficiency of the proposed control algorithm is significantly higher than that of the Standard model predictive control algorithm and Laguerre function-based model predictive control algorithm;the hardware memory occupied is much lower than that of the explicit model predictive control *** theoretical analysis and numerical verification, it was shown that this study can provide an effective solving scheme for füll thruster integrated control of large ring-column antenna satellites in oomplex space environment using onboard Computers with limited Computing power. © 2025 Chinese Vibration Engineering Society.

关键词： Geostationary satellites

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An integrated machine learning approach for identifying emergency rescue messages on social media during natural disasters

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Social Network Analysis and Mining 2025年第1期15卷 1-19页

作者： Khallouli, Wael Li, Jiang Huang, Jingwei Rabadi, Ghaith Kovacic, Samuel Department Engineering Management and Systems Engineering Old Dominion University NorfolkVA United States Department Electrical and Computer Engineering Old Dominion University NorfolkVA United States University of Texas Southwestern Medical Center DallasTX United States School of Modeling Simulation and Training University of Central Florida OrlandoFL United States

During large-scale disasters, emergency call centers are often overwhelmed by the large volume of rescue requests and calls for help. Consequently, people are turning to social media platforms to seek assistance. Rescue information posted on these platforms is extremely valuable for first responders to make informed rescue decisions. Therefore, the automatic identification of these requests from the vast amount of data posted on social media during crises is critical yet challenging. This work presents our ongoing research on applying deep learning techniques to extract actionable rescue information from social media during crises. We proposed a novel deep learning model that integrates a fine-tuned BERT to extract low-level statistical features and rule-based Regex filters to extract problem-specific features for emergency tweet identification. The proposed model was evaluated on labeled tweets collected from three hurricane events (Harvey, Ian, and Ida). Experimental results showed that our model performed better than several machine learning and deep learning methods in terms of the Area Under the Precision-Recall Curve (AUC-PR) metric for all events. This study contributed to the crisis informatics literature by introducing a novel deep learning approach for automatically identifying actionable information in social media, which can be adapted for similar natural language processing (NLP) tasks. © The Author(s) 2025.

关键词： Tweets

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UML-based combat effectiveness simulation system modeling within MDE

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Journal of systems Engineering and Electronics 2018年第6期29卷 1180-1196页

作者： ZHU Zhi LEI Yonglin SARJOUGHIAN Hessam LI Xiaobo ZHU Yifan Department of Military Modeling and Simulation School of Systems Engineering National University of Defense Technology Arizona Center for Integrated Modeling and Simulation School of Computing Informatics and Decision Systems EngineeringArizona State University

To reduce complexity, the combat effectiveness simulation system(CESS) is often decomposed into static structure,physical behavior, and cognitive behavior, and model abstraction is layered onto domain invariant knowledge(DIK) and application variant knowledge(AVK) levels. This study concentrates on the specification of CESS’s physical behaviors at the DIK level of abstraction, and proposes a model driven framework for efficiently developing simulation models within model-driven engineering(MDE). Technically, this framework integrates the four-layer metamodeling architecture and a set of model transformation techniques with the objective of reducing model heterogeneity and enhancing model continuity. As a proof of concept, a torpedo example is illustrated to explain how physical models are developed following the proposed framework. Finally, a combat scenario is constructed to demonstrate the availability, and a further verification is shown by a reasonable agreement between simulation results and field observations.

关键词： domain specific modeling model-driven development system engineering effectiveness simulation

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Enhancing realism in LiDAR scene generation with CSPA-DFN and linear cross-attention via Diffusion Transformer model

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Neural Networks 2025年 189卷 107503页

作者： Ye, Shaoxun Di, Xiaoguang Liao, Ming Li, Ximing Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China

Point cloud diffusion models have found extensive applications in autonomous driving and robotics. However, there is still a big gap between their generated LiDAR scene samples and real-world data in terms of visual quality. This discrepancy primarily arises from the loss of detailed information during the decoding process from latent space and the lack of guidance from global 3D structural information in the point cloud generation process, leading to distortions and artifacts in LiDAR scene samples. In this paper, we propose a novel LiDAR Diffusion Transformer Model that integrates Channel-Spatial Parallel Attention and Dilation Fusion Network (CSPA-DFN) with a linear cross-attention post-processing module to refine the generated LiDAR scene samples. Specifically, CSPA-DFN is designed to simultaneously emphasize detailed features across different channels and spatial locations in parallel, leveraging multi-scale dilated convolutions and channel grouping to preserve and enhance these detailed features. In order to provide global 3D structural information and balance performance and efficiency, we design a post-processing module that fuses voxelized features and range images using a linear ReLU cross-attention mechanism. Our approach is evaluated on the unconditional generation task using the KITTI-360 and nuScenes datasets, achieving the state-of-the-art results in LiDAR scene's generation quality. Furthermore, by incorporating semantic labels and camera views into the latent space, in addition to enhancing the model's semantic understanding capability for LiDAR scenes, our method also demonstrates additional performance improvements compared to previous works in terms of LiDAR scene's visual quality. The code implementation has been released on https://***/HITysx/LiDAR-Scene-Generation. © 2025 Elsevier Ltd

关键词： Photointerpretation

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Integrated Cellular Framework for modeling Ecosystems: Theory and Applications (vol 94, 213, 2017)

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simulation-TRANSACTIONS OF THE SOCIETY FOR modeling AND simulation INTERNATIONAL 2018年第9期94卷 NP1-NP1页

作者： Kazi, Baha Uddin Wainer, Gabriel Department of Systems and Computer Engineering Center for Visualization Simulation and Modeling Carleton University Canada

Integrated Cellular Framework for modeling Ecosystems: Theory and Applications', by Baha Uddin Kazi and Gabriel Wainer, published Online First on 11 March 2017 in the journal of simulation with the DOI: 10.1177/0037549717706007. In this paper, the funding statement was incorrect and the acknowledgements section was not added in the Online First version. This has since been corrected in the Online First version of the article.

关键词： Cell-DEVS modeling and simulation DEVS geographic information systems ecosystems

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A PARALLEL DOMAIN DECOMPOSITION METHOD FOR SOLVING ELLIPTIC EQUATIONS ON MANIFOLDS

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SIAM Journal on Scientific Computing 2025年第2期47卷 A916-A942页

作者： Qin, Lizhen Wang, Feng Wang, Yun School of Mathematics Nanjing University Nanjing210093 China Key Laboratory of Numerical Simulation of Large Scale Complex Systems Nanjing Normal University Ministry of Education Nanjing210023 China Jiangsu International Joint Laboratory of Big Data Modeling Computing and Application Nanjing Normal University Nanjing210023 China School of Mathematical Sciences Nanjing Normal University Nanjing210023 China School of Mathematical Sciences Center for Dynamical Systems and Differential Equations Soochow University Suzhou215006 China

We propose a new numerical domain decomposition method for solving elliptic equations on compact Riemannian manifolds. One advantage of this method is its ability to bypass the need for global triangulations or grids on the manifolds. Additionally, it features a highly parallel iterative scheme. To verify its efficacy, we conduct numerical experiments on some four-dimensional manifolds without and with boundary. © 2025 Society for Industrial and Applied Mathematics Publications. All rights reserved.

关键词： Domain decomposition methods

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Mechanical performance of recycled PVC window frames: An experimental and numerical investigation

Hybrid Advances

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Hybrid Advances 2025年 9卷

作者： Ait Khouya, Oumaima Sebbar, EL Hassan Elfarissi, Latifa Laaroussi, Najma University Hassan II of Casablanca Laboratory of modeling and Simulation of Intelligent Industrial Systems ENSET Mohammedia Morocco Technical Center of Plastic and Rubber Casablanca Morocco Institute for Research in Solar Energy and New Energies-IRESEN Morocco University Mohammed V in Rabat Material Energy and Acoustics Team (MEAT) EST Salé Morocco

PVC window frames are commonly used in the construction industry due to their durability, low cost, and ease of maintenance. However, with growing environmental concerns and the shift towards a circular economy, replacing virgin PVC with recycled materials in such applications has become a critical area of research. The recycling process as well as the source of waste, highly impact the quality of the recycled materials which limits its use in high-quality products. This study investigates the mechanical characterization of window profiles made from recycled PVC, focusing on their ability to withstand structural loads. Given that window frames are exposed to wind forces and building loads, ensuring their mechanical resistance is essential. The bending and tensile behavior of recycled PVC specimens were tested experimentally and numerically to assess the structural performance of the material under different loading conditions. A comparison between the results of numerical finite element simulations and those of experiments has been carried out to validate the findings. The results show that recycled PVC offers adequate mechanical and thermal performance for use in the manufacture of window profiles. © 2025

关键词： Circular economy Plastic recycling PVC PVC profile Window frame

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