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Global Satellite Navigation Distributed Synchronous Spoofing Monitoring Method based on Spatial Cross-correlation Spectrum

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IEEE Communications Letters 2025年第5期29卷 903-907页

作者： Wang, Chun Huang, Yan Huang, Yuxuan Kou, Yanhong Xi'an University of Architecture Technology School of Information and Control Engineering Xi'an710055 China Beihang University School of Electronics and Information Engineering Beijing100083 China

A novel distributed global satellite navigation synchronous spoofer, which is deployed as a pseudo-satellite constellation, sends several synchronous spoofing signals from different directions of arrival (DOAs). In this letter, we propose a synchronous spoofing monitoring method based on a spatial cross-correlation spectrum. The power and corresponding DOA measurements of those correlated sources are extracted by searching for the peak of the proposed cross-correlation spectrum. Experimental results demonstrate that the proposed method enables the simultaneous estimation of three essential features, such as DOAs, received power levels, and cross-correlations among different navigation signals, and effectively detects the synchronous spoofing signal at the moment when the monitoring correlation coefficients reach the maximum of 1. © 2025 IEEE.

关键词： Direction of arrival

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Eco-driving model for Wireless Charging Scenario of connected and automated electric freight vehicles based on differentiated driving strategies at multi-intersections 4

Eco-driving model for Wireless Charging Scenario of connecte...

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2024 4th International Conference on Intelligent Traffic Systems and Smart City, ITSSC 2024

作者： Wang, Wenbo Fang, Shujing Hui, Fei Zhang, Junfei School of Information Engineering Chang’an University Xi’an710064 China School of Electronics and Control Engineering Chang’an University Xi’an710064 China

ISBN: (纸本)9781510686304

Due to their environmentally friendly and energy-saving characteristics, electric freight vehicles (EFVs) have emerged as indispensable and significant modes of urban transportation. However, the limited driving range of vehicles often leads to low transportation efficiency. In this research, an eco-driving model is introduced specifically tailored for connected and autonomous electric freight vehicles (CAEFVs). This model incorporates wireless charging technology by deploying wireless charging lanes at multiple signalized intersections, allowing CAEFVs to replenish energy while moving slowly at traffic lights. At the same time, differentiated passage strategies are designed to meet the charging requirements of different vehicles while ensuring uninterrupted passage through intersections. The traffic benefits of these passage strategies are analyzed considering different initial speeds and wireless charging areas (WCA). The study reveals that the charging-optimum mode (COM) outperforms the time-optimum mode (TOM) in terms of charging efficiency, albeit requiring longer travel times. This study offers valuable insights into the implementation of wireless charging infrastructure for CAEFVs, with the potential to enhance their driving range capabilities. © 2025 SPIE. All rights reserved.

关键词： Wireless charging

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Cut-in scenarios generation on highways for autonomous driving tests 4

Cut-in scenarios generation on highways for autonomous drivi...

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2024 4th International Conference on Intelligent Traffic Systems and Smart City, ITSSC 2024

作者： Fang, Shujing Wang, Wenbo Hui, Fei School of Information Engineering Chang’an University Xi’an710064 China School of Electronics and Control Engineering Chang’an University Xi’an710064 China

ISBN: (纸本)9781510686304

Autonomous driving test scenarios are the basis of autonomous driving virtual simulation tests. In this study, we take the right lane change cut-in scenario of adjacent lanes on highways in the highD dataset as an example, and based on the pure transformer architecture, we propose a method that combines CNN-GRU to capture the time series features and introduces MH-ESA to increase the smoothing, which is called LC-GAN, for generating the autonomous vehicles cut-in scenarios while driving on highways. Experiments show that LC-GAN is more advantageous in terms of data fidelity and usability compared to TimeGAN and COSCI-GAN, in addition to similarity improvements of 19.02% and 20.34%, respectively. As the number of generated scenarios increased from 1540 to 20,000, the coverage rate from 87.31% to 93.90%, it shows that the proposed method can effectively generalize the generation of cut-in scenarios for autonomous driving test, which lays the foundation for generating test scenarios and advancing autonomous driving test. © 2025 SPIE.

关键词： Gallium nitride

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Analysis of pedestrian motion and trajectory across different urban environments 4

Analysis of pedestrian motion and trajectory across differen...

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2024 4th International Conference on Intelligent Traffic Systems and Smart City, ITSSC 2024

作者： Zhang, Junfei Hui, Fei Wang, Wenbo Fan, Yingchun Liu, Xiyao School of Information Engineering Chang'an University Xi'an710064 China School of Electronics and Control Engineering Chang'an University Xi'an710064 China College of Information Engineering Northwest A&F University Shaanxi Yangling712199 China

ISBN: (纸本)9781510686304

Understanding pedestrian behavior in urban environments is essential for advancing autonomous driving technologies and intelligent transportation systems. This study investigates the motion and trajectories of pedestrians across three distinct urban settings: free walk, shared space, and urban road. We analyze motion characteristics such as speed and acceleration, employing statistical methods, and examine pedestrian trajectories including average curvature, average speed, and proportion of stop points. Our findings reveal significant variations in pedestrian behavior across these environments. Urban road exhibits lower speeds, higher curvature, and frequent starts and stops, whereas shared space shows a lower proportion of stop points. These insights underscore the importance of adapting autonomous driving systems to diverse environmental contexts to enhance safety and efficiency. © 2025 SPIE.

关键词： Autonomous vehicles

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Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem

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Complex System Modeling and Simulation 2025年第1期5卷 86-106页

作者： Wang, Juan Zhang, Guanghui Li, Xiaoling Feng, Yanxiang School of Information Science and Technology Hebei Agricultural University Baoding071001 China Xi'an Jiaotong University State Key Laboratory for Manufacturing Systems Engineering Xi'an710049 China School of Electronics and Control Engineering Chang'an University Xi'an710064 China School of Automation Science and Engineering Xi'an Jiaotong University Xi'an710049 China

In this research, a novel dynamic and heterogeneous identity based cooperative co-evolutionary algorithm (DHICCA) is proposed for addressing the distributed lot-streaming flowshop scheduling problem (DLSFSP) with the objective to minimize the makespan. A two-layer-vector representation is devised to bridge the solution space of DLSFSP and the search space of DHICCA. In the evolution of DHICCA, population individuals are endowed with heterogeneous identities according to their quality, including superior individuals, ordinary individuals, and inferior individuals, which serve local exploitation, global exploration, and diversified restart, respectively. Because individuals with different identities require different evolutionary mechanisms to fully unleash their respective potentials, identity-specific evolutionary operators are devised to evolve them in a cooperative co-evolutionary way. This is important to use limited population resources to solve complex optimization problems. Specifically, exploitation is carried out on superior individuals by devising three exploitative operators with different intensities based on techniques of variable neighborhood, destruction-construction, and gene targeting. Exploration is executed on ordinary individuals by a newly constructed discrete Jaya algorithm and a probability crossover strategy. In addition, restart is performed on inferior individuals to introduce new evolutionary individuals to the population. After the cooperative co-evolution, all individuals with different identities are merged as a population again, and their identities are dynamically adjusted by new evaluation. The influence of parameters on the algorithm is investigated based on design-of-experiment and comprehensive computational experiments are used to evaluate the performance of all algorithms. The results validate the effectiveness of special designs and show that DHICCA performs more efficient than the existing state-of-the-art algorithms in solving

关键词： Vector spaces

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TIPS:Tailored information Extraction in Public Security Using Domain-Enhanced Large Language Model

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Computers, Materials & Continua 2025年第5期83卷 2555-2572页

作者： Yue Liu Qinglang Guo Chunyao Yang Yong Liao School of Cyber Science and Technology University of Science and Technology of ChinaHefei230026China National Engineering Research Center for Public Safety Risk Perception and Control by Big Data China Academy of Electronics and Information TechnologyBeijing100041China

Processing police incident data in public security involves complex natural language processing(NLP)tasks,including information *** data contains extensive entity information—such as people,locations,and events—while also involving reasoning tasks like personnel classification,relationship judgment,and implicit ***,utilizing models for extracting information from police incident data poses a significant challenge—data scarcity,which limits the effectiveness of traditional rule-based and machine-learning *** address these,we propose *** collaboration with public security experts,we used de-identified police incident data to create templates that enable large language models(LLMs)to populate data slots and generate simulated data,enhancing data density and *** then designed schemas to efficiently manage complex extraction and reasoning tasks,constructing a high-quality dataset and fine-tuning multiple open-source *** showed that the fine-tuned ChatGLM-4-9B model achieved an F1 score of 87.14%,nearly 30%higher than the base model,significantly reducing error *** corrections further improved performance by 9.39%.This study demonstrates that combining largescale pre-trained models with limited high-quality domain-specific data can greatly enhance information extraction in low-resource environments,offering a new approach for intelligent public security applications.

关键词： Public security information extraction large language model prompt engineering

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Multi-scale network for single image deblurring based on ensemble learning module

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Multimedia Tools and Applications 2025年第11期84卷 9045-9064页

作者： Wu, WenBo Pan, Yun Su, Na Wang, JingTao Wu, ShaoChuan Xu, ZeKun Yu, YouJian Liu, YaPeng State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China School of Computer and Cyberspace Security Communication University of China Beijing100024 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China College of Computer and Control Engineering Northeast Forestry University Harbin150040 China School of Computer and Information Engineering Tianjin Chengjian University Tianjin300384 China School of Computer Science and Technology Anhui University Hefei230601 China

In this paper, we have identified two primary issues with current multi-scale image deblurring methods. On the one hand, the blurring scale is ignored. On the other hand, the context information of images is not fully utilized, and the spatial detail information of images is lost. To better solve the above problems, on top of that, this paper proposes a multi-scale network for single image deblurring. The designed network contains two parts: 1) Ensemble Learning Model: The Weak Learning Model in this module connects multiple weak learners in series to increase network depth. Moreover, through multi-scale feature ensemble module, the output features and intermediate features of different weak learner are integrated, and finally strong learner is used to enhance the features with semantic information at different scales;2) Spatial Feature Enhancement Module: This module can preserve spatial detail information of images and compensate for the disadvantages of losing image spatial details due to continuous downsampling in the Ensemble Learning Model structure. Our proposed deblurring model has been extensively evaluated on several benchmark datasets, and the model achieves superior performance compared to the most advanced deblurring methods. In particular, the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) values are 33.57 dB and 0.965 on the GoPro dataset, respectively, with PSNR and SSIM improving by 0.49 dB and 0.002 over NAFNet, and 0.65 dB and 0.004 over Restormer. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Learning systems

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Linear Convergent Distributed Nash Equilibrium Seeking With Compression

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IEEE Transactions on Automatic control 2025年第5期70卷 3316-3323页

作者： Chen, Xiaomeng Wu, Yuchi Yi, Xinlei Huang, Minyi Shi, Ling Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China College of Electronics and Information Engineering Tongji University Department of Control Science and Engineering Shanghai201804 China Massachusetts Institute of Technology Lab for Information & Decision Systems CambridgeMA02139 United States Carleton University School of Mathematics and Statistics OttawaONK1S 5B6 Canada

information compression techniques are majorly employed to reduce communication cost over peer-to-peer links. In this article, we investigate distributed Nash equilibrium (NE) seeking problems in a class of noncooperative games over directed graphs with information compression. To improve communication efficiency, a compressed distributed NE seeking (C-DNES) algorithm is proposed to obtain an NE for games, where the differences between decision vectors and their estimates are compressed. The proposed algorithm is compatible with a general class of compressors, including both unbiased and biased compressors. Moreover, our approach only requires the adjacency matrix of the directed graph to be row-stochastic, in contrast to past works that relied on balancedness or specific global network parameters. It is shown that C-DNES not only inherits the advantages of conventional distributed NE algorithms, achieving linear convergence rate for games with restricted strongly monotone mappings, but also saves communication costs in terms of transmitted bits. Finally, numerical simulations illustrate the advantages of C-DNES in saving communication cost by an order of magnitude under different compressors. © 1963-2012 IEEE.

关键词： Stochastic systems

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OSSR: Online Scalable Scheduling and Routing for Industrial Time-Sensitive Networking

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IEEE Transactions on Network Science and engineering 2025年第3期12卷 1761-1775页

作者： Xu, Lei Xu, Qimin Zhang, Yanzhou Wang, Shouliang Chen, Cailian Guan, Xinping Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Shanghai Jiao Tong University Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Shanghai200240 China Shanghai Jiao Tong University School of Electronics Information and Electrical Engineering Shanghai200240 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Jiao Tong University SJTU-Paris Elite Institute of Technology Shanghai200240 China

As the promising deterministic networking technology of Industrial Internet of Things (IIoT), Time-Sensitive Networking (TSN) has been widely investigated in recent years. Most existing research focuses on offline scheduling and routing for TSN, which is time-consuming and thus unsuitable for dynamic stream demands. To tackle this problem, an online scalable scheduling and routing (OSSR) scheme is proposed for TSN in this paper. A novel slot occupancy representation (SOR) model is established based on divisibility theory to transform the clique-based to a three-level tree-based mode in complex IIoT scenarios. This transformation reduces the computational complexity of maximum slot occupancy judgment from exponential to linear complexity. Based on the above SOR model, a load balance metric for stream scheduling is constructed to guide the optimal routing. Assessed by this metric, an online decoupled routing and scheduling algorithm is proposed to minimize the maximum slot occupancy of all links while guaranteeing high scalability. Evaluation results show that the proposed OSSR scheme outperforms the existing approaches with better adaption to dynamics and lower slot occupancy of links. © 2013 IEEE.

关键词： Scheduling algorithms

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Sim2Real Learning With Domain Randomization for Autonomous Guidewire Navigation in Robotic-Assisted Endovascular Procedures

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IEEE Transactions on Automation Science and engineering 2025年 22卷 13842-13854页

作者： Yao, Tianliang Wang, Haoyu Lu, Bo Ge, Jiajia Pei, Zhiqiang Kowarschik, Markus Sun, Lining Seneviratne, Lakmal Qi, Peng Tongji University College of Electronics and Information Engineering Shanghai Institute of Intelligent Science and Technology Department of Control Science and Engineering Shanghai200092 China Shanghai University of Engineering Science School of Electronic and Electrical Engineering Shanghai201620 China Soochow University Robotics and Microsystems Center School of Mechanical and Electrical Engineering Jiangsu Suzhou215131 China Advanced Therapies Siemens Healthineers Ltd. Shanghai201318 China University of Shanghai for Science and Technology Oriental Pan-Vascular Devices Innovation College Shanghai200093 China Bavaria Forchheim91301 Germany Khalifa University KUCARS Department of Mechanical and Nuclear Engineering Abu Dhabi United Arab Emirates Tongji University College of Electronics and Information Engineering Shanghai Institute of Intelligent Science and Technology State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center Shanghai East Hospital Department of Control Science and Engineering School of Medicine Shanghai200092 China

Over the past decade, significant advancements have been made in the research and industrialization of robotic systems for endovascular procedures, yet their clinical application remains relatively limited. Physicians commonly report that these robots lack certain intelligent assistive capabilities during procedures. There has been increasing interest and attempts to apply learning-centered algorithms to the training and enhancement of surgical robot skills. This paper proposes an autonomous navigation algorithm for interventional guidewires that is initially trained solely in a virtual simulation environment and subsequently deployed to a real-world robot. Experimental results demonstrate the feasibility of this approach for real-world applications. The proposed approach can help physicians reduce the learning curve for guidewire manipulation and elevate the robot to a higher level of autonomous operation, thereby breaking through the current bottleneck in the level of intelligence for clinical applications of interventional robots. It also holds promise for bringing intelligent transformation to future interventional procedures. © 2004-2012 IEEE.

关键词： Adversarial machine learning

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