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第43届中国控制会议

作者： Wang Shenhang Tian Kun Zheng Wei Liu Mengyu National Key Laboratory of Science and Technology on Aerospace Intelligent Control

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In modern industry,fault detection is very important in high-cost and safety-critical *** component analysis(PCA) is an effective data-driven approach which is widely used in this *** PCA is time-invariant,which often lead to false *** order to overcome the false alarms,recursive PCA algorithms have been proposed for adaptive ***,the amount of calculation of the algorithm is very great because of frequently updated *** this paper,a novel recursive PCA method is proposed for solving the question by introducing the standard residual *** standard residual method serves as an indicator of the level of consistency among data,which is used to decide whether or not to update the PCA *** proposed method is applied to fault detection and experiment results demonstrate the effectiveness of the method.

关键词： Principal component analysis fault detection standard residual method

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Robust Target Detection and Localization for UAV Autonomous Landing with Partially Occluded Targets 15th

Robust Target Detection and Localization for UAV Autonomous ...

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Shao, Mingmei Liu, Yanyan Tang, Jiaze Liu, Huanyu Li, Junbao Faculty of Computing Harbin Institute of Technology Harbin150080 China National Key Laboratory of Electromagnetic Space Security Tianjin300308 China Electrical Measurement Technology and Intelligent Control Institute School of Instrumentation Science and Engineering Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9789819700677

This paper presents an approach for robust target detection and localization in the context of UAV autonomous landing with partially occluded targets. Since the performance of the autonomous landing system largely depends on the accurate detection and positioning of the landing target, it is very important to deal with the local occlusion caused by obstacles or environmental factors. In order to improve the overall performance of the system, we propose a fault-tolerant target detection method and target completion strategy. The proposed target detection method combines image processing technology with feature extraction algorithm, which can recognize and locate the landing target even in the case of occlusion. The target completion strategy aims to recover the missing part of the occluded target and make the detection and location algorithm execute more reliably. We perform experiments on image data sets with different horizontal object occlusion to evaluate the performance of the proposed method. The results show that our method successfully detects and locates the landing target under different occlusion levels, and significantly improves the performance of UAV autonomous landing system in the real scene. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Obstacle Avoidance Trajectory Correction control Method for Hopping Movement on Small Celestial Bodies

Obstacle Avoidance Trajectory Correction Control Method for ...

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第43届中国控制会议

作者： Zhe Yang Xizhen Gao Shengying Zhu School of Aerospace Engineering Beijing Institute of Technology National Key Laboratory of Science and Technology on Space Intelligent Control

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The surface of small celestial bodies is characterized by complex morphology and irregular gravitational *** rover faces the risk of colliding with obstacles during the hopping movement,and environmental disturbances and initial errors can lead to trajectory *** response to the issue,this paper proposes an obstacle avoidance trajectory correction control method during hopping movement of the ***,the obstacle avoidance correction potential function is *** maneuver moment is determined by setting limits on trajectory errors,obstacle warning boundaries,and potential function *** the minimization of the potential field value at the final landing point as the performance metric,the analytical solution for the maneuver velocity during obstacle avoidance correction is derived by solving the linearized dynamic ***,simulation results for hopping movement on simulated surface and a small celestial body model are presented,demonstrating the effectiveness of the method in steering the rover avoiding obstacles,correcting trajectory errors,and improving hopping accuracy.

关键词： Hopping movement Obstacle avoidance Trajectory correction Potential function

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Joint state-sharing and truncation BCJR for power-efficient coherent optical interconnections utilizing symbol-rate sampling DSP over a hollow-core fiber

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Optics Letters 2025年第10期50卷 3461-3464页

作者： Wang, Chenchen Li, Zhipei Dong, Ze Gao, Ran Song, Junyuan Mai, Tianle Guo, Dong Chang, Huan Pan, Xiaolong Zhu, Lei Xin, Xiangjun School of Information and Electronics Beijing Institute of Technology Beijing100081 China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing100081 China School of Integrated Circuits Beijing University of Posts and Telecommunications Beijing100876 China

Power-efficient digital signal processing (DSP) architectures are indispensable for enabling the sustainable scalability of optical networks in next-generation data center interconnects (DCIs). This paper introduces a minimalist symbol-rate sampling (SRS) DSP framework for coherent optical systems, seamlessly integrated with a hollow-core fiber (HCF) to enable ultra-low-complexity signal processing. The core of this framework is the joint state-sharing and truncation Bahl–Cocke–Jelinek–Raviv (JSST-BCJR) algorithm, which enhances hardware efficiency by eliminating up to 91% of state-space computations, significantly reducing computational complexity while maintaining negligible performance degradation. Experimental validation confirms the feasibility of the proposed minimalist SRS-DSP framework through the successful transmission of a 100-Gbaud 16QAM signal over 20.6 km of HCF. This work underscores the viability of SRS-DSP in power-constrained DCIs and highlights the synergistic integration of low-complexity DSP and HCF, offering a pathway toward power-efficient, high-throughput optical networks. © 2025 Optica Publishing Group. All rights are reserved.

关键词： Network coding

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Tracking and Mapping Strategy for Indoor UAV Based on Entropy Theory:An ORB-SLAM3 Extension 41

Tracking and Mapping Strategy for Indoor UAV Based on Entrop...

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第41届中国控制会议

作者： Jian Xu Haoyu Qi Min Xu Yunge Zang Zhen Li Xi Zhang Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

For indoor application,which is an entirely GPS-denied environment,visual simultaneous localization and mapping(SLAM) facilitates the real autonomy of unmanned aerial vehicle(UAV) but raises the challenging requirement on accurate localization with low computational *** address this difficulty,a stereo-camera based SLAM system is proposed by applying Entropy theory to *** an extension to ORB-SLAM3,the additional entropy decision module and map processor are specifically *** decision module can improve computing efficiency by deciding whether keyframes or extra optimization should be ***,the map processor is targeted at loading and maintaining the prior map whenever *** results in indoor laboratory environment show that the developed system can achieve the superior localization accuracy in more efficient computation manner with smaller size of mapping compared with ***,the map can be effectively expanded and corrected even when prior information is invalid,greatly increasing the robustness of SLAM system.

关键词： UAV stereo-camera ORB-SLAM3 entropy theory prior map

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A Range Alignment Method Using Deep Learning for MMW ISAR Imaging 1

A Range Alignment Method Using Deep Learning for MMW ISAR Im...

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1st International Conference on the Frontiers of Electronic, Electrical and Information Engineering, ICFEEIE 2024

作者： Zhao, Chaofan Ma, Chunguang Chen, Xu Luo, Yong School of Electronic Science and Engineering University of Electronic Science Technology of China Sichuan Chengdu China School of Electronic Science and Engineering UESTC Chengdu Sichuan China State Key Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing China

ISBN: (纸本)9798331528300

Range alignment is an important step in the imaging process of inverse synthetic aperture radar (ISAR) radar. In this paper, a novel deep learning network model is proposed to effectively tackle the challenge of distance alignment in millimeter-wave (MMW) ISAR imaging. The proposed model leverages a multi-layer bidirectional long short-term memory (bi-LSTM) network architecture to learn intricate features among echoes, thus facilitating precise alignment along the range direction. Meanwhile transfer learning was used to enhance the adaptability of the model to multiple signal-to-noise ratios (SNR). Experiment results show that the aligned images generated by proposed model in this paper are closer to the reference images in low SNR environments compared to traditional methods. ©2024 IEEE.

关键词： Radar imaging

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Safe Efficient Policy Optimization Algorithm for Unsignalized Intersection Navigation

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 2011-2026页

作者： Xiaolong Chen Biao Xu Manjiang Hu Yougang Bian Yang Li Xin Xu State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body the College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body the College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082 Wuxi Intelligent Control Research Institute(WICRI)of Hunan University Wuxi 214115China College of Intelligence Science and Technology Institute of Unmanned SystemsNational University of Defense TechnologyChangsha 410073China

Unsignalized intersections pose a challenge for autonomous vehicles that must decide how to navigate them safely and *** paper proposes a reinforcement learning(RL)method for autonomous vehicles to navigate unsignalized intersections safely and *** method uses a semantic scene representation to handle variable numbers of vehicles and a universal reward function to facilitate stable learning.A collision risk function is designed to penalize unsafe actions and guide the agent to avoid them.A scalable policy optimization algorithm is introduced to improve data efficiency and safety for vehicle learning at *** algorithm employs experience replay to overcome the on-policy limitation of proximal policy optimization and incorporates the collision risk constraint into the policy optimization *** proposed safe RL algorithm can balance the trade-off between vehicle traffic safety and policy learning *** intersection scenarios with different traffic situations are used to test the algorithm and demonstrate its high success rates and low collision rates under different traffic *** algorithm shows the potential of RL for enhancing the safety and reliability of autonomous driving systems at unsignalized intersections.

关键词： Autonomous driving decision-making reinforcement learning(RL) unsignalized intersection

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Design of Wide Stopband and High Suppression Cavity Filter 24

Design of Wide Stopband and High Suppression Cavity Filter

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Zhao, Junyu Ma, Chunguang Zhou, Jinghan Li, Junhui Liu, Jiaming Luo, Yong School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China State Key Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China

ISBN: (纸本)9781665473217

Radio frequency filter is the core device to improve the signal to noise ratio of radar. A cavity filter for suppressing high harmonics in Ka band millimeter wave (MMW) radar is presented. The structural parameters of the filter are obtained by theoretical calculation. A cavity filter with the center frequency of 8.1 GHz and the relative bandwidth of 9.80% is designed by using HFSS electromagnetic simulation software. The spurious passband is above twice the frequency of the center frequency. The attenuation of the stopband is greater than 78 dB in 9.2 16 GHz, which can well meet the demand of the need of Ka band MMW radar to suppress high harmonics. © 2023 IEEE.

关键词： Electromagnetic simulation

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Research on lightweight detection algorithm of Infrared Image based on YOLOv5 4

Research on lightweight detection algorithm of Infrared Imag...

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4th International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2024

作者： Zhang, Wenyi Mo, Hongwei Wu, Songling Li, Xiaomin Harbin Engineering University School of Intelligent Science and Engineering Harbin150000 China Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing100854 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

At present, infrared image can show good detection effect in complex environment because of its unique imaging characteristics, which brings a lot of convenience to people's production and life. However, because the infrared image contains a great lot of unnecessary information, it has great requirements for computing power and memory capacity, so it is challenging to satisfy the demands of real-time detection on resource-constrained portable mobile devices. To solve this problem, this paper proposes a refined lightweight algorithm built upon the YOLOv5, which changes the backbone network of the model to GhostNet network, introduces CA attention mechanism into the model to improve the detection effect of small targets, and changes the loss function of the model to Focal-EIoU loss function to improve the location effect of the boundary box and quicken the model's rate of convergence. Then replace the conventional convolution used in the sampling process of the model with the space-to-depth convolution module, in order to enhance the model's detection performance on low-resolution images and enable the extraction of more feature information. According to the experimental results, the enhanced detection algorithm is just 1% less than the initial YOLOv5 algorithm, and the model volume and floating point calculation are reduced by 31.9% and 36% respectively. This is better suited for deployments that are lightweight. © 2024 SPIE.

关键词： Convolution

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