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information Processing and Network Provisioning (ICIPNP), International Conference on

作者： Zuting Chen Shuai Han Peng Yu Chenyu Wu Huan Li Harbin Institute of Technology Information and Communication Engineering Harbin China Beijing Institute of Spacecraft System Engineering Beijing China National Key Laboratory of Electromagnetic Space Safety Beijing China

ISBN: (数字)9798350363470

ISBN: (纸本)9798350363487

With the vigorous development of low orbit satellite internet, the advantage of wide area coverage in satellite communication can effectively compensate for the limited coverage capacity of ground cellular networks. Therefore, studying how ground users can access the low Earth orbit satellite internet and how to allocate resources after access is an important part of the implementation of the space-air-ground integrated network. On the other hand, since entering the AI era, deep learning has always provided rich possibilities for solving various problems. Therefore, achieving the allocation of satellite power between satellite to ground links based on deep learning has important research significance. This paper discusses a model for users to access satellite networks nearby, and establishes an optimization problem for satellite power allocation with the goal of maximizing satellite network capacity. Since the downlink channel fading of low orbit satellites mainly comes from path loss, the geographic location information of satellites and ground stations can be used as input features for neural networks to learn power allocation methods. This paper constructs a forward propagation neural network and trains it in a supervised manner. Through simulation, it can be proven that the neural network proposed in this paper can effectively allocate satellite downlink power at a lower algorithm complexity.

关键词： Deep learning Training Satellites Approximation algorithms Downlink Space-air-ground integrated networks Orbits Complexity theory Resource management Optimization

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Single-Photon LiDAR Depth Estimation Based on Time Series Correlation

Single-Photon LiDAR Depth Estimation Based on Time Series Co...

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Academic International Symposium on Optoelectronics and Microelectronics technology (AISOMT)

作者： Lin Ruobin Sun Jianfeng Jiang Peng Ma Le Zhou Xin Ren Zhen Ding Ji National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin Heilongjiang China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou Henan China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Tianjin Jinhang Technical Physics Institute Tianjin China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (数字)9798331542283

ISBN: (纸本)9798331542290

With advancements in science and technology, photon-counting LiDAR applications are growing due to long-range measurement, high-definition imaging, and accuracy. Geiger-mode avalanche photodiodes (Gm-APD) provide single-photon sensitivity and picosecond resolution, but noise in depth estimation affects imaging accuracy. This study introduces a novel depth estimation method using time series correlation to mitigate these noise issues, improving accuracy in LiDAR imaging. Utilizing a photon-counting LiDAR system and time-correlated single photon counting (TCSPC), this study capture target echo photon flight times to maintain depth information. The proposed denoising approach incorporates multiple time series windows and Bayesian estimation to enhance depth accuracy, alongside a pruning algorithm to optimize computational efficiency. Evaluation metrics show significant improvements: RSNR improved by 4% and MAE decreased by 43 % compared to traditional methods. The findings demonstrate the robustness of this method across various scenarios, enhancing depth estimation and noise mitigation in photon-counting LiDAR technology, thereby providing practical improvements for a range of applications.

关键词： Correlation Laser radar Accuracy Filtering Depth measurement Time series analysis Noise reduction Imaging Bayes methods Photonics

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TSN Disciplined Oscillators for Time Synchronization in Distributed Networks

TSN Disciplined Oscillators for Time Synchronization in Dist...

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Asia communications and Photonics Conference and Exhibition (ACP)

作者： Zhifu Li Guochu Shou Xiaodong Zhang Li Chen Dong Zhao Xiaoyu Zhao Kai Xia Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China

This paper proposes a TSNDO scheme utilizing time-sensitive networking to discipline clocks, providing precise time for distributed networks. The experimental results demonstrate that TSNDO achieves the time accuracy ... 详细信息

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

关键词： Accuracy Asia Prototypes Optical fiber communication Calibration Synchronization Oscillators Photonics Clocks

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Time Error Bound of Deterministic Transmission in Cross-Domain Time-Sensitive Networking

Time Error Bound of Deterministic Transmission in Cross-Doma...

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Asia communications and Photonics Conference and Exhibition (ACP)

作者： Hao Ma Hongxing Li Li Chen Dong Zhao Xiaoyu Zhao Kai Xia Guochu Shou Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China

Based on coupled network theory, a bounded time error model for network determinism is proposed. The limit of traffic scheduling performance affected by time synchronization error in cross-domain time-sensitive networ... 详细信息

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

关键词： Asia Prototypes Logic gates Optical fiber communication Delays Planning Synchronization Time factors Photonics Business

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Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning 22

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Cao, Weipeng Yao, Xuyang Xu, Zhiwu Pan, Yinghui Sun, Yixuan Li, Dachuan Qiu, Bohua Wei, Muheng Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9798331527471

Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model’s capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods. © 2024 IEEE.

关键词： Zero-shot learning

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A Reinforcement Learning PID Compound Protocol Design Method for Ultrasonic Motor control*

A Reinforcement Learning PID Compound Protocol Design Method...

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control Conference (ANZCC), Australian and New Zealand

作者： Qiang Wang Yunlong Yang Xiongjun Wu Jinqi Wang Guanyu Liu The 802 Institute of Shanghai Academy of Space Flight Technology The Eighth Academy of China Aerospace Science and Technology Corporation National Defense Key Laboratory of Science and Technology on Electromagnetic Scattering Shanghai Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

Aiming at overcoming drawback brought by the nonlinear and time-varying characteristics of ultrasonic motor, this paper proposed a PID compound controller of ultrasonic motor based on reinforcement learning to improve the dynamic performance and adaptability of the system. In practice, the output control value of the reinforcement learning controller is observed in general to be uncertain, and sometimes even destroys the learning strategy, which makes the system unstable. To overcome this limitation, this paper ultilized the idea of expert rules to improve the controller performance, and the Lyapunov stability is also guaranteed. The simulation results show that the improved composite control algorithm can significantly improve the learning efficiency, and meanwhile shorten the number of learning iterations. At the same time, the composite controller based on expert rules significantly improves the control performance of the system, in terms of reducing the rise time and adjustment time of the system, as well as reducing the steady-state error of the system.

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Suppression of Adverse Effects of Transmission Clearance in Brushless DC Motor Servo systems by Switching Compensation*

Suppression of Adverse Effects of Transmission Clearance in ...

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control Conference (ANZCC), Australian and New Zealand

作者： Dao Zhou Yunlong Yang Xiongjun Wu Biao Liu Shanghai Aerospace Control Technology Research Institute Shanghai China The 802 Institute of Shanghai Academy of Space Flight Technology The Eighth Academy of China Aerospace Science and Technology Corporation National Defense Key Laboratory of Science and Technology on Electromagnetic Scattering Shanghai Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

In conventional servo system with transmission mechanisms, the transmission backlash seems to be an inevitable phenomenon in many applications. Excessive backlash can lead to relative motion between the servo motor and the load, resulting in response delays, instability, and oscillations, consequently causing a decline in the dynamic performance of the system. To mitigate the negative effects of transmission backlash, this paper proposes a model-based backstepping adaptive control algorithm and a switching compensation approach tailored to transmission backlash. A feed-forward control gap compensation method is suggested. Leveraging identified servo system parameter information, this method achieves compensation and suppression of the nonlinearity caused by backlash. The efficacy of the proposed method is verified through theoretical analysis and simulation experiments, which also guaranteed its capability to effectively enhance the tracking accuracy and stability of the servo system while suppressing undesirable phenomena caused by backlash.

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Robust UAV Path Planning with Obstacle Avoidance for Emergency Rescue

arXiv

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arXiv 2025年

作者： Mao, Junteng Jia, Ziye Gu, Hanzhi Shi, Chenyu Shi, Haomin He, Lijun Wu, Qihui The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing211106 China National Mobile Communications Research Laboratory Southeast University Jiangsu Nanjing211111 China The School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China

The unmanned aerial vehicles (UAVs) are efficient tools for diverse tasks such as electronic reconnaissance, agricultural operations and disaster relief. In the complex three-dimensional (3D) environments, the path planning with obstacle avoidance for UAVs is a significant issue for security assurance. In this paper, we construct a comprehensive 3D scenario with obstacles and no-fly zones for dynamic UAV trajectory. Moreover, a novel artificial potential field algorithm coupled with simulated annealing (APF-SA) is proposed to tackle the robust path planning problem. APF-SA modifies the attractive and repulsive potential functions and leverages simulated annealing to escape local minimum and converge to globally optimal solutions. Simulation results demonstrate that the effectiveness of APF-SA, enabling efficient autonomous path planning for UAVs with obstacle avoidance. Copyright © 2025, The Authors. All rights reserved.

关键词： Antennas

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Robust UAV Path Planning with Obstacle Avoidance for Emergency Rescue

Robust UAV Path Planning with Obstacle Avoidance for Emergen...

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2025 IEEE Wireless communications and Networking Conference, WCNC 2025

作者： Mao, Junteng Jia, Ziye Gu, Hanzhi Shi, Chenyu Shi, Haomin He, Lijun Wu, Qihui Nanjing University of Aeronautics and Astronautics The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Jiangsu Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Jiangsu Nanjing211111 China The School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China

ISBN: (纸本)9798350368369

The unmanned aerial vehicles (UAVs) are efficient tools for diverse tasks such as electronic reconnaissance, agricultural operations and disaster relief. In the complex three-dimensional (3D) environments, the path planning with obstacle avoidance for UAVs is a significant issue for security assurance. In this paper, we construct a comprehensive 3D scenario with obstacles and no-fly zones for dynamic UAV trajectory. Moreover, a novel artificial potential field algorithm coupled with simulated annealing (APF-SA) is proposed to tackle the robust path planning problem. APF-SA modifies the attractive and repulsive potential functions and leverages simulated annealing to escape local minimum and converge to globally optimal solutions. Simulation results demonstrate that the effectiveness of APFSA, enabling efficient autonomous path planning for UAVs with obstacle avoidance. © 2025 IEEE.

关键词： Drones

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Precise Timing over Beyond 5G Networks for Intelligent Transport in the Smart City

Precise Timing over Beyond 5G Networks for Intelligent Trans...

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IEEE International Symposium on Personal, Indoor and Mobile Radio communications (PIMRC)

作者： Hongxing Li Guochu Shou Yaqiong Liu Yihong Hu State Key Laboratory of Networking and Switching Technology School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

The need for precise timing is increasing with the development of the smart city, and intelligent transport is a key application that often relies on the distribution of accurate timing. Existing time synchronization solutions cannot adequately meet the precise timing needs for practical applications in intelligent transportation. Global Navigation Satellite systems (GNSS) signals, for instance, can be obstructed, weakened, or deflected in urban canyon environments. While certain sectors like telecommunications and smart grids have successfully adopted IEEE 1588 for high-precision time synchronization, its dependence on standalone networks and limited application within local area networks poses challenges when catering to the wide-ranging and mobile demands of intelligent transportation applications. This paper categorizes the time synchronization requirements of intelligent transport and proposes a time synchronization scheme over converged networks, which separates time transmission and precision compensation based on software-defined networking (SDN) principles, and makes it possible to provide precise timing for intelligent transport devices, including on-board units (OBUs) and roadside units (RSUs), over wired and wireless communication networks. Experimental results indicate that the proposed scheme achieves a relative time error of less than 1.2 microseconds over the converged networks.

关键词： Wireless communication Global navigation satellite system Accuracy Smart cities Transportation Telecommunications Smart grids Synchronization Software defined networking Local area networks

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