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Intelligent Reflecting Surface-Assisted Combined TOA and AOA Localization Algorithm

KSII Transactions on Internet and Information Systems 2025年第4期19卷 1357-1373页

作者： Zhang, Yuexia Gang, Yuanshuo Duan, Shiru Wang, Yu Key Laboratory of Modern Measurement and Control Technology Beijing Information Science and Technology University Beijing102206 China Key Laboratory of Information and Communication Systems Beijing Information Science and Technology University Beijing102206 China

Wireless positioning technology plays a crucial role in various applications, including intelligent transportation, industrial automation, and smart cities. However, in non-line-of-sight environments, signal obstruction and multipath effects significantly degrade localization accuracy. To address these challenges, this paper proposes an Intelligent Reflecting Surface-assisted Combined time of arrival (TOA) and angle of arrival (AOA) Localization (IRS-CTAL) algorithm. Specifically, this paper introduces a dynamic partially connected IRS structure, which selectively activates IRS sub-arrays in a time-division manner. This dynamic activation mitigates multipath interference and enhances the controllability of IRS-reflected signals, leading to improved localization performance. In the proposed IRS-CTAL algorithm, the 2D multiple signal classification algorithm is employed to jointly estimate the TOA and AOA of the received signals. Furthermore, to optimize the estimated coordinates and minimize the localization error, this paper incorporates the root mean square propagation algorithm, which efficiently corrects nonlinear distortions caused by IRS reflections. Simulation results demonstrate that the IRS-CTAL algorithm significantly outperforms traditional localization methods, achieving an average localization error reduction of 41% compared to the direct geometric computation method. Copyright © 2025 KSII.

关键词： Computational geometry

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Fully Distributed Low-Complexity UAV Formation control with Fixed-Time Full-State Error Performance

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IEEE Access 2025年 13卷 68224-68231页

作者： Yu, Pengfei Li, Qing Beijing Information Science and Technology University School of Automation Beijing100192 China Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing100101 China

This paper presents a fully distributed, low-complexity UAV formation controller design with fixed-time full-state error performance, which is able to address the difficulties in obtaining global information and suppressing external disturbances without observer or adaptive law in existing solutions. The position of neighboring UAVs is the only information to be exchanged, and desired state observer is not required, thereby reducing communication costs, which is well-suited to larger-scale UAV formation systems. The proposed control scheme has the capability to handle external disturbances without observer or adaptive law, simplifying the controller's design and implementation process, reducing computational burden. Moreover, by imposing fixed-time performance constraints on tracking error and virtual error, fixed-time formation tracking error and virtual velocity tracking error can be achieved, which also improves the response speed and accuracy of UAV formation, making it more capable of meeting the time requirements of actual tasks and adapting to dynamically changing environments. Additionally, all closed-loop signals are rigorously proven to be semi-globally ultimately uniformly bounded. Finally, numerical simulation is conducted to verify the effectiveness of proposed control scheme. © 2013 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Defective Ground Structure Design for Reducing Coupling between Microstrip Antenna Arrays

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Progress in Electromagnetics Research C 2025年 151卷 123-130页

作者： Xu, Junhao Wang, Yafei Wang, Xiaozhe Li, Zhensong Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing100101 China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China

In order to reduce the coupling between dense antenna arrays in multiple input multiple output (MIMO) systems, this paper proposes a method to reduce the coupling between microstrip antenna arrays by utilizing a defected ground structure (DGS), which consists of "W"-shaped slits etched in the ground plane. Simulation results show that the structure can achieve −46.6 dB isolation between antenna arrays. To verify the effectiveness of the structure, the microstrip antenna arrays loaded with this DGS are fabricated and measured, and the measured results are consistent with the simulated ones, which verifies the effectiveness of the structure. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Antenna arrays

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Joint Task Offloading and Resource Allocation Strategy for Space-Air-Ground Integrated Vehicular Networks

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1027-1043页

作者： Yuanshuo Gang Yuexia Zhang Zhihai Zhuo School of Information and Communication Engineering Beijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100101China

Space-Air-Ground integrated Vehicular Network(SAGVN)aims to achieve ubiquitous connectivity and provide abundant computational resources to enhance the performance and efficiency of the vehicular ***,there are still challenges to overcome,including the scheduling of multilayered computational resources and the scarcity of spectrum *** address these problems,we propose a joint Task Offloading(TO)and Resource Allocation(RA)strategy in SAGVN(namely JTRSS).This strategy establishes an SAGVN model that incorporates air and space networks to expand the options for vehicular TO,and enhances the edge-computing resources of the system by deploying edge *** minimize the system average cost,we use the JTRSS algorithm to decompose the original problem into a number of subproblems.A maximum rate matching algorithm is used to address the channel allocation and the Lagrangian multiplier method is employed for computational *** acquire the optimal TO decision,a differential fusion cuckoo search algorithm is *** simulation results demonstrate the significant superiority of the JTRSS algorithm in optimizing the system average cost.

关键词： edge computing Resource Allocation(RA) Space-Air-Ground integrated Vehicular Network(SAGVN) Task Offloading(TO)

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A Study for Inter-Satellite Cooperative Computation Offloading in LEO Satellite Networks

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China Communications 2025年第2期22卷 12-25页

作者： Gang Yuanshuo Zhang Yuexia Wu Peng Zheng Hui Fan Guangteng Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 102206China 2 National Innovation Institute of Defense Technology Academy of Military ScienceBeijing 100071China

Low Earth orbit(LEO)satellite networks have the advantages of low transmission delay and low deployment cost,playing an important role in providing reliable services to ground *** paper studies an efficient inter-satellite cooperative computation offloading(ICCO)algorithm for LEO satellite ***,an ICCO system model is constructed,which considers using neighboring satellites in the LEO satellite networks to collaboratively process tasks generated by ground user terminals,effectively improving resource utilization ***,the optimization objective of minimizing the system task computation offloading delay and energy consumption is established,which is decoupled into two *** terms of computational resource allocation,the convexity of the problem is proved through theoretical derivation,and the Lagrange multiplier method is used to obtain the optimal solution of computational *** deal with the task offloading decision,a dynamic sticky binary particle swarm optimization algorithm is designed to obtain the offloading decision by *** results show that the ICCO algorithm can effectively reduce the delay and energy consumption.

关键词： computation offloading inter-satellite co-operation LEO satellite networks

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Adaptive Multi-Objective Shift Strategy for Heavy-duty Vehicle Based on Performance State Evaluation of the Transmission Mechanism

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IEEE Transactions on Instrumentation and measurement 2025年

作者： Wang, Liyong Huang, Xiaozan Wu, Jianpeng Li, Pengpeng Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100192 China

Heavy tracked vehicles frequently operate in intricate and demanding driving conditions, where the powertrain, a core component, inevitably experiences performance degradation due to mileage accumulation. This degradation not only undermines vehicle reliability but also constrains the full utilization of its capabilities. To address these challenges, this study proposes a multi-objective optimization approach to developing an adaptive shift strategy that balances the vehicle’s power, fuel economy, and reliability performance. The optimization problem is tackled using the NSGA-II algorithm, which generates the Pareto front of shift speeds by considering the vehicle’s power, economy, and reliability performance. The optimal shift speeds are adaptively selected based on the transmission mechanism performance states, which are calculated using the fuzzy comprehensive evaluation model. During acceleration from 0 to 80 km/h, total friction work is reduced by 6.59% and 23% when the performance state scores are 70 and 40, respectively, compared to a score of 90. Additionally, the maximum jerk is reduced by 45.07% at a score of 40 compared to a score of 90. These reductions in friction work and jerk decrease wear on the transmission mechanism system, thus improving vehicle reliability. © 1963-2012 IEEE.

关键词： Automobile transmissions

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Data-Driven Prediction of Coefficient of Friction in Wet Friction Components: A Model Development and Interpretability Analysis

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Journal of Tribology 2025年第7期147卷 074601页

作者： Wu, Jianpeng Zhao, Peng Cui, Jiahao Wang, Liyong Yang, Chengbing Ouyang, Jianping Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University 12 Xiaoying East Road Haidian District Beijing100192 China School of Mechanical and Engineering University of Science and Technology Beijing 30 Xueyuan Road Haidian District Beijing100083 China Mechanical Electrical Engineering School Beijing Information Science and Technology University 12 Xiaoying East Road Haidian District Beijing100192 China

Predicting the coefficient of friction (COF) is essential for enhancing the efficiency and reliability of mechanical systems. Nevertheless, traditional mechanistic models relying on fixed values or fitted curves fail to accurately capture this complexity. To address this issue, this paper proposes a model for predicting the COF of wet friction components using an extreme gradient boosting (XGBoost) algorithm optimized by the sparrow search algorithm (SSA). This model effectively captures the nonlinear relationships among relative speed, pressure, temperature, and COF. As a result, the proposed SSA-XGBoost model exhibits excellent predictive performance with a root mean square error (RMSE) of only 0.063, and 88.3% of the COF predictions have a relative error of less than 1%, significantly outperforming other deep-learning algorithms. Additionally, to enhance the understanding of the COF prediction results for wet friction components, the SHapley Additive exPlanations (SHAP) model is used to explore the influence of relative speed, pressure, and temperature on the predicted COF values. Copyright © 2024 by ASME.

关键词： Deep learning

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Green anti-solvent modulation of the growth of binary FAXMA1-X tin-based perovskite and their photovoltaic properties

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The European Physical Journal B 2025年第1期98卷 1-11页

作者： Deng, Longtao He, Linfeng Chen, Xinyao Cheng, Jin Zhang, Chunqian Li, Zhenjun Li, Junming Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China Beijing Key Laboratory for Sensor School of Science Beijing Information Science and Technology University Beijing China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing China CAS Key Laboratory of Standardization and Measurement for Nanotechnology CAS Key Laboratory of Nanophotonic Materials and Devices (Preparatory) National Center for Nanoscience and Technology Beijing China

Tin-based perovskite represents a highly promising alternative to lead-based perovskite, offering a number of significant advantages. These include non-toxicity, high absorbance, and excellent photovoltaic properties. The use of the toxic anti-solvent chlorobenzene (CBZ) in the preparation of tin-based perovskite thin films has the dual disadvantage of increasing the environmental hazards and the cost of subsequent treatment. The use of acetic acid (HAc) as a green anti-solvent has been demonstrated to effectively regulate the crystallization process of tin-based perovskite FASnI3, resulting in the preparation of perovskite films of superior quality. To further enhance the performance of tin-based perovskite, Zhao et al., organic cation mixing was used to add MAI to the FASnI3 system and optimize the ratio, resulting in an optimal ratio of FA (0.75) MA (0.25) (FA = NH2CH = NH2+, MA = CH3NH3+) (Zhao et al. Adv Sci 4(11):1700204, 2024). In this study, we choose the crystallization process during the preparation of binary FA0.75MA0.25SnI3 perovskite using a green anti-solvent HAc. The findings demonstrated that HAc was capable of influencing the crystallization of binary tin-based perovskite, facilitating the formation of perovskite films with minimal pinholes and enhanced uniformity and crystallinity. Additionally, the resulting perovskite exhibits a band gap of 1.35 eV, which is in close alignment with the predicted ideal band gap as postulated by Schottky's theory. Furthermore, it displays enhanced hydrophobic properties. In the binary perovskite photovoltaic device prepared using the anti-solvent HAc, the maximum device efficiency reached 3.62%. The findings of this study will contribute to the understanding of the crystallization process of diverse perovskite materials in the presence of a green anti-solvent.

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GFADE: generalized feature adaptation and discrimination enhancement for deepfake detection

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PeerJ Computer Science 2025年 11卷 e2879-e2879页

作者： Tian, ZhiYong Yi, Junkai School of Automation Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

With the rapid advancement of deep generative techniques, such as generative adversarial networks (GANs), the creation of realistic fake images and videos has become increasingly accessible, raising significant security and privacy concerns. Although existing deepfake detection methods perform well within a single dataset, they often experience substantial performance degradation when applied across datasets or manipulation types. To address this challenge, we propose a novel deepfake detection framework that combines multiple loss functions and the MixStyle technique. By integrating Cross-Entropy Loss, ArcFace loss, and Focal Loss, our model enhances its discriminative power to better handle complex forgery characteristics and effectively mitigate data imbalance. Additionally, the MixStyle technique introduces diverse visual styles during training, further improving the model’s generalization across different datasets and manipulation scenarios. Experimental results demonstrate that our method achieves superior detection accuracy across a range of cross-dataset and cross-manipulation tests, significantly improving model robustness and generalizability. Copyright 2025 Tian and Yi Distributed under Creative Commons CC-BY 4.0

关键词： Generative adversarial networks

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An enhanced nonlinear fatigue cumulative damage model based on toughness exhaustion and strength degradation

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International Journal of Fatigue 2025年 198卷

作者： Yu, Yifan Wang, Liyong Wu, Jianpeng Chang, Shuyuan Zhang, Ximing Key Laboratory of Advanced Manufacturing Technology Beijing University of Technology Beijing100124 China Key Laboratory of Modern Measurement and Control Technology in Ministry of Education Beijing Information Science and Technology University Beijing100192 China Science and Technology on Vehicle Transmission Laboratory China North Vehicle Research Institute Beijing100072 China

Accurate prediction of fatigue life under variable amplitude (VA) loading remains fundamentally challenged by load-sequence-dependent damage accumulation in metallic structures. This study establishes a nonlinear cumulative damage model integrating toughness exhaustion and strength degradation mechanisms through damage equivalence principles. Multi-level VA experiments on carbon steel, alloy steel, and aerospace aluminum alloys demonstrate that the proposed model reduces life prediction errors to 6.53% (5-level) and 9.43% (8-level), achieving 93.94% and 94.79% accuracy improvement versus the Palmgren-Miner method. Statistical evaluations reveal dominant control of two key factors: material ultimate tensile strength (UTS) and stress amplitude differential between successive cycles. These advancements provide validated engineering tools for durability assessment of aero-engine components and military vehicle systems experiencing complex mission profiles. © 2025 Elsevier Ltd

关键词： Aluminum alloys

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