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Domain Adaptation-based Radio Frequency Fingerprint Identification for Industrial Cyber-Physical Systems

IEEE Network 2025年

作者： Wang, Yatong Cao, Bin Wen, Zhongyi Yan, Mu Song, Changqing Beijing Institute of Technology School of Information and Electronics Beijing100081 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100191 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100191 China

With the widespread adoption of cloud and fog platforms, security issues facing Industrial Cyber-Physical Systems (ICPSs) are increasingly prominent. Radio Frequency Fingerprinting (RFFI) emerges as a promising physical layer security technique for user authentication, effectively enhancing ICPS security over wireless networks by exploiting inherenthardware imperfections in transmitters. However, as technologies evolve and user environments become denser and more complex, existing RFFI techniques encounter significant domain shift challenges, leading to performance degradation. Therefore, developing domain-adaptive RFFI techniques is crucial for the effectiveness of ICPSs. In this article, we first provide a comprehensive review of the RFFI framework, emphasizing its applications in ICPSs and the key processes involved. Next, we focus on the domain shift issues faced by RFFI in ICPSs and present a comprehensive survey of domain adaptation methods. To tackle these challenges, we propose a novel feature-alignment based domain adaptation (FADA) framework for RFFI, which is designed to mitigate the performance degradation caused bycross-domain shifts by aligning the feature representations of the source and target domain. Finally, we discuss the inherent challenges and future directions for developing domain adaptation based RFFI to enhance the security of ICPSs. © 2025 IEEE. All rights reserved.

关键词： Radio frequency identification (RFID)

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Text-Image Scene Graph Fusion for Multimodal Named Entity Recognition

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2828-2839页

作者： Cheng, Jian Long, Kaifang Zhang, Shuang Zhang, Tian Ma, Lianbo Cheng, Shi Guo, Yinan State Key Laboratory for Intelligent Coal Mining and Strata Control Research Institute of Mine Big Data Chinese Institute of Coal Science Beijing100013 China Northeastern University College of Software Shenyang110819 China Shaanxi Normal University College of Computer Science Xi'an710062 China China University of Mining and Technology Xuzhou221116 China

With the popularity and widespread use of social media platforms, such as Twitter and Facebook, massive amounts of text and image information posted by a variety of users have flooded these social media platforms. Thus, multimodal named entity recognition (MNER) has become a research hotspot for the task of extracting named entities from multimodal data. Empirically, the visual clues unrelated to text data may introduce uncertain or even negative impacts on the named entity recognition. The considerations of the relevance of multimodal data have been ignored in the previous studies. In this article, to effectively measure the relationship between text data and visual cues for improving the accuracy of named entities, we propose a text-image scene graph fusion (TISGF) approach with a text-image similarity assessment module (TISA) and a text-image fusion module (TIF) for MNER. Specifically, we first construct two (visual and textual) scene graphs to exploit the joint features of objects and relations in text and image and encode the two scene graphs separately using a specific encoder pair. In this way, we can obtain both object-level and relationship-level cross-modal features. Subsequently, TISA is used to compute the similarity of the image and text data and to determine the proportion of visual information that will be retained for fusion. Finally, we use TIF to achieve a unified multimodal representation of each word and predict the entity type using conditional random fields. Extensive experiment results on two public datasets demonstrate the effectiveness and competitiveness of our proposed method for the MNER task. © 2020 IEEE.

关键词： Semantics

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Fog Images Generation About Unmanned Surface Vessels with Improved Generative Adversarial Network 42

Fog Images Generation About Unmanned Surface Vessels with Im...

引用

42nd Chinese control Conference, CCC 2023

作者： Tang, Yifeng Huang, Zhihui Tang, Chuancong Luo, Chuanshang Xu, Yifan Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

This paper proposes a fog weather data augmentation method for the unmanned surface vessels (USVs) via improved Generative Adversarial Network(GAN) model. First, a generator scheme for GAN is proposed with the guided generation of the atmospheric scattering model in this paper. A Laplacian Pyramid Based Depth Residuals model is added to the generator which reduces the difficulty of generating fog images caused by the degradation of water surface image and improves the quality of generated images. Finally, fog images are generated from sunny weather images collected with HUST-12C by LPBDR-GAN model and experiments show that generated images are very close to real fog images. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Generative adversarial networks

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Adaptive Non-backstepping Output-Feedback control for Hydraulic Servo System Subject to Uncertain Dynamics 19th

Adaptive Non-backstepping Output-Feedback Control for Hydrau...

引用

19th Chinese intelligent Systems Conference, CISC 2023

作者： Li, Chenghuan Ma, Jun Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming University of Science and Technology Kunming650500 China

ISBN: (纸本)9789819968855

In this paper, a novel non-backstepping adaptive control approach is presented for the hydraulic servo systems, aiming to mitigate the "explosion of complexity" issue and achieve matching of full-state known conditions. This approach enables one-step control through coordinate transformation. To address the control singularity problem, two radial basis function neural networks (RBFNNs) are utilized to estimate the separate sets of lumped unknown dynamics. Additionally, an adaptive controller is designed where the neural network weights are updated online using a weight error variable. This ensures that the estimated weights converge closely to their true values, allowing for accurate identification of the unknown dynamics. Theoretical analysis and numerical simulation are conducted verity the correctness and effectiveness of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Backstepping

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CognitiveDrone: A VLA Model and Evaluation Benchmark for Real-Time Cognitive Task Solving and Reasoning in UAVs

arXiv

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arXiv 2025年

作者： Lykov, Artem Serpiva, Valerii Khan, Muhammad Haris Sautenkov, Oleg Myshlyaev, Artyom Tadevosyan, Grik Yaqoot, Yasheerah Tsetserukou, Dzmitry The Intelligent Space Robotics Laboratory Center for Digital Engineering Skolkovo Institute of Science and Technology Russia

This paper introduces CognitiveDrone, a novel Vision-Language-Action (VLA) model tailored for complex Unmanned Aerial Vehicles (UAVs) tasks that demand advanced cognitive abilities. Trained on a dataset comprising over 8,000 simulated flight trajectories across three key categories—Human Recognition, Symbol Understanding, and Reasoning—the model generates real-time 4D action commands based on first-person visual inputs and textual instructions. To further enhance performance in intricate scenarios, we propose CognitiveDrone-R1, which integrates an additional Vision-Language Model (VLM) reasoning module to simplify task directives prior to high-frequency control. Experimental evaluations using our open-source benchmark, CognitiveDroneBench, reveal that while a racing-oriented model (RaceVLA) achieves an overall success rate of 31.3%, the base CognitiveDrone model reaches 59.6%, and CognitiveDrone-R1 attains a success rate of 77.2%. These results demonstrate improvements of up to 30% in critical cognitive tasks, underscoring the effectiveness of incorporating advanced reasoning capabilities into UAV control systems. Our contributions include the development of a state-of-the-art VLA model for UAV control and the introduction of the first dedicated benchmark for assessing cognitive tasks in drone operations. The complete repository is available at https://***. © 2025, CC BY-NC-ND.

关键词： Visual languages

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Millimeter-Wave Full-Duplex Phased Array RF Self-Interference Cancellation technology

Millimeter-Wave Full-Duplex Phased Array RF Self-Interferenc...

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IEEE International Conference on Communications Workshops, ICC

作者： Yang Li Wensheng Pan Gezu Jiwu Chengzhe Shi Nanzhou Hu Shihai Shao National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

In the integrated access and backhaul (IAB) base stations, a model of large-scale antenna arrays is established to address the problem of radio frequency self-interference cancellation (RFSIC) in millimeter-wave (mmW) full-duplex (FD) systems. The characteristics of the SI under the condition of separating the receiving and transmitting antenna arrays are analyzed. This paper simplifies the RFSIC model using the equivalent delay method, while an RFSIC model applicable to the received beamforming synthesis is proposed. The RFSIC performance under different tap numbers is also compared by simulation experiments. The simulation results show that the RFSIC ability of the 16 taps is greater than 50 dB for the SI with a carrier frequency of 26.5 GHz and a bandwidth of 200 MHz. Furthermore, the proposed method is tested and verified in a real scenario, and the test results show that the RFSIC ability is greater than 35 dB when 16 taps are used for SI reconstruction. Combined with digital self-interference cancellation (DSIC), the error vector magnitude (EVM) can be effectively increased by 30.8 dB, while the phased array system can realize FD communication.

关键词： Phased arrays Interference cancellation Simulation Conferences Millimeter wave technology Full-duplex system Bandwidth

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A Method to Enhance Data Observability for Robot Calibration in Confined space 19th

A Method to Enhance Data Observability for Robot Calibration...

引用

19th Chinese intelligent Systems Conference, CISC 2023

作者： Zhang, Qinglong Gao, Guanbin Liu, Fei Xing, Yashan Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming650500 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming University of Science and Technology Kunming650500 China

ISBN: (纸本)9789819968855

Kinematic calibration is crucial for enhancing the accuracy of robots. However, in production environments, limited space often hinders the deployment of measurement instruments. To address this challenge and improve robot calibration accuracy, a novel approach combining optimization algorithms and reference linkages is proposed. This method tackles issues such as small variations in calibration data and poor generalization. By integrating a reference linkage at the end flange, the diversity of the robot’s joint angles is increased. An observability optimization algorithm is utilized to select the optimal measurement configurations, resulting in calibration data with improved observability. Through simulations conducted in both confined and large spaces, the effectiveness of the proposed method in enhancing calibration performance is verified. The results show that this method significantly improves the observability of calibration data in confined space, and enhances the accuracy and generalization capability of robot calibration. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Observability

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UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation

arXiv

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arXiv 2025年

作者： Sautenkov, Oleg Yaqoot, Yasheerah Lykov, Artem Mustafa, Muhammad Ahsan Tadevosyan, Grik Akhmetkazy, Aibek Cabrera, Miguel Altamirano Martynov, Mikhail Karaf, Sausar Tsetserukou, Dzmitry Intelligent Space Robotics Laboratory Center for Digital Engineering Skolkovo Institute of Science and Technology Russia

The UAV-VLA (Visual-Language-Action) system is a tool designed to facilitate communication with aerial robots. By integrating satellite imagery processing with the Visual Language Model (VLM) and the powerful capabilities of GPT, UAV-VLA enables users to generate general flight paths-and-action plans through simple text requests. This system leverages the rich contextual information provided by satellite images, allowing for enhanced decision-making and mission planning. The combination of visual analysis by VLM and natural language processing by GPT can provide the user with the path-and-action set, making aerial operations more efficient and accessible. The newly developed method showed the difference in the length of the created trajectory in 22% and the mean error in finding the objects of interest on a map in 34.22 m by Euclidean distance in the K-Nearest Neighbors (KNN) approach. The code is available here: https://***/sautenich/uav-vla © 2025, CC BY-NC-ND.

关键词： Visual languages

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Asteroid Image Inpainting Method Based on Accelerated Diffusion Model

Asteroid Image Inpainting Method Based on Accelerated Diffus...

引用

6th International Conference on intelligent Computing and Signal Processing (ICSP)

作者： Yunyun Zheng Xiangyu Huang Space Intelligence Control Laboratory Beijing Institute of Control Engineering Science and Technology Beijing China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

To mitigate the threat of asteroid impact on life on Earth, non-nuclear kinetic energy high-speed impact has been identified as the most viable strategy. To ensure accurate impact on the asteroid's center of mass with maximum kinetic energy, high-precision and high-speed autonomous optical navigation is necessary during the probe's approach to the asteroid. Autonomous optical navigation is crucial due to the difficulty of using historical tracking data such as astrometry on the ground, given the long distance between the asteroid and the probe. The navigation image is used to extract the centroid of the target asteroid, with the center of gravity of the asteroid profile serving as the impact point to provide a stable impact direction. It is important to note that asteroids have irregular shapes, fast spin, and rapidly changing bright regions. The shadow area of the asteroid is constantly changing due to illumination, which causes bias in the impact point due to the incomplete profile. To complete the contour of the target asteroid, a method based on the accelerated diffusion model (ADM) is proposed to inpainting the shadow area. ADM is fast enough for mission and has been found to have the highest accuracy index and the lowest centroid deviation after restoration when compared to several advanced image restoration methods.

关键词： Accuracy Navigation Optical imaging Diffusion models Adaptive optics Solar system Image restoration Kinetic energy Probes High-speed optical techniques

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ImpedanceGPT: VLM-driven Impedance control of Swarm of Mini-drones for intelligent Navigation in Dynamic Environment

arXiv

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arXiv 2025年

作者： Batool, Faryal Zafar, Malaika Yaqoot, Yasheerah Khan, Roohan Ahmed Khan, Muhammad Haris Fedoseev, Aleksey Tsetserukou, Dzmitry Intelligent Space Robotics Laboratory Center for Digital Engineering Skolkovo Institute of Science and Technology Russia

Swarm robotics plays a crucial role in enabling autonomous operations in dynamic and unpredictable environments. However, a major challenge remains ensuring safe and efficient navigation in environments filled with both dynamic alive (e.g., humans) and dynamic inanimate (e.g., non-living objects) obstacles. In this paper, we propose ImpedanceGPT, a novel system that combines a Vision-Language Model (VLM) with retrieval-augmented generation (RAG) to enable real-time reasoning for adaptive navigation of mini-drone swarms in complex environments. The key innovation of ImpedanceGPT lies in the integration of VLM and RAG, which provides the drones with enhanced semantic understanding of their surroundings. This enables the system to dynamically adjust impedance control parameters in response to obstacle types and environmental conditions. Our approach not only ensures safe and precise navigation but also improves coordination between drones in the swarm. Experimental evaluations demonstrate the effectiveness of the system. The VLM-RAG framework achieved an obstacle detection and retrieval accuracy of 80% under optimal lighting. In static environments, drones navigated dynamic inanimate obstacles at 1.4 m/s but slowed to 0.7 m/s with increased separation around humans. In dynamic environments, speed adjusted to 1.0 m/s near hard obstacles, while reducing to 0.6 m/s with higher deflection to safely avoid moving humans. © 2025, CC BY-NC-SA.

关键词： Visual languages

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