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IEEE International Workshop on Electromagnetics, Applications and Student Innovation (iWEM)

作者： Min Wang Xuan Li Dongsheng Mo Zhengchuan Chen Postdoctoral Research Center of Chongqing Key Laboratory of Optoelectronic Information Sensing and Transmission Technology Chongqing University of Posts and Telecommunications Chongqing China Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory Guilin University of Electronic Technology Guilin China University of Electronic Science and Technology of China Chengdu China School of Microelectronics and Communication Engineering Chongqing University Chongqing China

This article demonstrates a wideband SIW slot antenna with gain-enhancing capability. The upper layer of SIW is composed of a 50 Ω microstrip line and radiation slots. The radiation slots are composed of a multiple branch slot and a couple of oblique slots. The multiple branch slot can excite triple resonant modes for extending impedance matching bandwidth and gain, while the oblique slots are utilized to match the microwave line so that further enhancing the impedance matching bandwidth. Simulated results of the SIW slot antenna indicate that the relative bandwidth is up to 16.7%. The gain at 9.0 GHz reaches 9.3 dBi, while the 1-dB gain bandwidth reaches 25.5%.

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Information Reconciliation for Continuous-Variable Quantum Key Distribution Beyond the Devetak-Winter Bound Using Short Blocklength Error Correction Codes

arXiv

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arXiv 2024年

作者： Gümüş, Kadir dos Reis Frazão, João Albores-Mejia, Aaron Škorić, Boris Liga, Gabriele Can Gültekin, Yunus Bradley, Thomas Alvarado, Alex Okonkwo, Chigo High Capacity Optical Transmission Laboratory Electro-Optical Communications Group Eindhoven University of Technology Eindhoven5600 MB Netherlands CubiQ Technologies De Groene Loper 5 Eindhoven Netherlands Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven5600 MB Netherlands Information and Communication Theory Lab Signal Processing Group Eindhoven University of Technology 5600MB Netherlands

In this paper we introduce a reconciliation protocol with a two-step error correction scheme using a short blocklength low rate code and a long blocklength high rate code. We show that by using this two-step decoding method it is possible to achieve secret key rates beyond the Devetak-Winter bound. We simulate the protocol using short blocklength low-density parity check code, and show that we can obtain reconciliation efficiencies up to 1.5. Using these high reconciliation efficiencies, it is possible double the achievable distances of CV-QKD systems. © 2024, CC BY.

关键词： Quantum cryptography

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Unsupervised Domain-Adaptive Semantic Segmentation for Surgical Instruments Leveraging Dropout-Enhanced Dual Heads and Coarse-Grained Classification Branch

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical Robotics and Bionics 2025年

作者： Li, Ziqian Wang, Zhengyu Xu, Xinzhou Chen, Yongfa Schuller, Bjorn W. Hefei University of Technology School of Mechanical Engineering Hefei China Nanjing University of Posts and Telecommunications School of Internet of Things Nanjing China Graz University of Technology Signal Processing and Speech Communication Laboratory Graz Austria Chair of Health Informatics Munich Germany Munich Data Science Institute Munich Germany Munich Center for Machine Learning Munich Germany Imperial College London GLAM – the Group on Language Audio and Music London United Kingdom

Accurate semantic segmentation for surgical instruments is crucial in robot-assisted minimally invasive surgery, mainly regarded as a core module in surgical-instrument tracking and operation guidance. Nevertheless, it is usually difficult for existing semantic surgical-instrument segmentation approaches to adapt to unknown surgical scenes, particularly due to their insufficient consideration for reducing the domain gaps across different scenes. To address this issue, we propose an unsupervised domain-adaptive semantic segmentation approach for surgical instruments, leveraging Dropout-enhanced Dual Heads and Coarse-Grained classification branch (D2HCG). The proposed approach comprises dropout-enhanced dual heads for diverse feature representation, and a coarse-grained classification branch for capturing complexities across varying granularities. This incorporates consistency loss functions targeting fine-grained features and coarse-grained granularities, aiming to reduce crossscene domain gaps. Afterwards, we perform experiments in crossscene surgical-instrument semantic segmentation cases, with the experimental results reporting the effectiveness for the proposed approach, compared with state-of-the-art semantic segmentation ones. © 2018 IEEE.

关键词： coarse-grained classification dropout enhancement Surgical instruments unsupervised domain-adaptive semantic segmentation

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Selecting Discriminative Features for Fine-Grained Visual Classification 5th

Selecting Discriminative Features for Fine-Grained Visual Cl...

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5th Asian Conference on Pattern Recognition, ACPR 2019

作者： Xu, Qin Li, Linyang Chen, Qian Luo, Bin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China

ISBN: (纸本)9783030414030

Fine-grained visual classification is a challenging task because of intra-class variation and inter-class similarity. Most fine-grained models predominantly focus on discriminative region localization which can effectively solve the intra-class variation, but ignore global information and the problem of inter-class similarity which easily leads to overfitting on specific samples. To address these issues, we develop an end-to-end model based on selecting discriminative features for fine-grained visual classification without the help of part or bounding box annotations. In order to accurately select discriminative features, we integrate effective information from different receptive fields to enhance the quality of features, then the features of discriminative regions detected by anchors and the whole image’s feature are jointly processed for classification. Besides, we propose a new loss function to optimize the model to find discriminative regions and prevent overfitting in the particular sample, which can simultaneously solve the problems of intra-class variation and inter-class similarity. Comprehensive experiments show that the proposed approach is superior to the state-of-the-art methods on CUB-200-2011, Stanford Cars and FGVC-Aircraft datasets. © Springer Nature Switzerland AG 2020.

关键词： Classification (of information)

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A Low Computational Complexity DOA Estimation using Sum/difference Pattern based on DNN

Research Square

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Research Square 2021年

作者： Xu, Saiqin Chen, Baixiao Xiang, Houhong National Laboratory of Radar Signal Processing Xidian University Shaanxi Xi'An China School of Computer and Information Hefei University of Technology Hefei Anhui He'fei China

Tracking low-elevation targets over an uneven surface is challenging because of the complicated and volatile multipath signals. Multipath signals cause the amplitude and phase distortion of direct signal, which degrades the performance and generates mismatch between existing classical multipath signal and actual model. Machine learning-based methods are data-driven, they do not rely on prior assumptions about array geometries, and are expected to adapt better to array imperfections. The amplitude comparison Direction-of-Arrival (DOA) algorithm performs a few calculations, has a simple system structure, and is widely used. In this paper, an efficient DOA estimation approach based on Sum/Difference pattern is merged with deep neural network. Fully learn the potential features of the direct signal from the echo signal. In order to integrate more phase features, the covariance matrix is applied to the amplitude comparison algorithm, it can accommodate multiple snapshot signals instead of a single pulse automatically. The outputs of the deep neural network (DNN) are concatenated to reconstruct a covariance matrix for DOA estimation. Moreover, the superiority in computational complexity and generalization of proposed method are proved by simulation experiments compared with state-of-the-art physics-driven and data-driven methods. Field data sets acquired from a VHF array radar are carried out to verify the proposed method satisfies practicability in the severe multipath effect. © 2021, CC BY.

关键词： Deep neural networks

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Cross-Modal Object Tracking via Modality-Aware Fusion Network and A Large-Scale Dataset

arXiv

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arXiv 2023年

作者： Liu, Lei Zhang, Mengya Li, Cheng Li, Chenglong Tang, Jin The Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China The Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Intelligent Computing and Signal Processing The Ministry of Education Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China The School of Computer Science and Technology Anhui University Hefei230601 China

Visual tracking often faces challenges such as invalid targets and decreased performance in low-light conditions when relying solely on RGB image sequences. While incorporating additional modalities like depth and infrared data has proven effective, existing multi-modal imaging platforms are complex and lack real-world applicability. In contrast, near-infrared (NIR) imaging, commonly used in surveillance cameras, can switch between RGB and NIR based on light intensity. However, tracking objects across these heterogeneous modalities poses significant challenges, particularly due to the absence of modality switch signals during tracking. To address these challenges, we propose an adaptive cross-modal object tracking algorithm called Modality-Aware Fusion Network (MAFNet). MAFNet efficiently integrates information from both RGB and NIR modalities using an adaptive weighting mechanism, effectively bridging the appearance gap and enabling a modality-aware target representation. It consists of two key components: an adaptive weighting module and a modality-specific representation module. The adaptive weighting module predicts fusion weights to dynamically adjust the contribution of each modality, while the modality-specific representation module captures discriminative features specific to RGB and NIR modalities. MAFNet offers great flexibility as it can effortlessly integrate into diverse tracking frameworks. With its simplicity, effectiveness, and efficiency, MAFNet outperforms state-of-the-art methods in cross-modal object tracking. To validate the effectiveness of our algorithm and overcome the scarcity of data in this field, we introduce CMOTB, a comprehensive and extensive benchmark dataset for cross-modal object tracking. CMOTB consists of 61 categories and 1000 video sequences, comprising a total of over 799K frames. We believe that our proposed method and dataset offer a strong foundation for advancing cross-modal object tracking research. The dataset, toolkit, a

关键词： Large dataset

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Acoustic Compact Test Range System for Large-Scale Target Characteristic Testing in a Shorter Distance

SSRN

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SSRN 2022年

作者： Wang, Jie Lin, Hai Zhang, Qi Guo, Huaihai Ge, Junxiang School of Electronics and Information Nanjing University of Information Science and Technology Nanjing210044 China School of Marine Sciences Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Key Laboratory of Meteorological Observation and Signal Processing Nanjing University of Information Science and Technology Nanjing210044 China

In the acoustic scattering and characteristic tests of large targets and large-scale transducers, in order to meet the plane wave conditions, the larger test distance is often required. It is a greater difficulty for the testing laboratories with limited space. In order to compact the testing distance and solve the problem of requiring a long distance for large-scale target scattering and large-scale transducer testing, based on the principle and application of microwave compact test rang system and the approximation of electromagnetic wave and acoustic wave, an underwater acoustic compact range test system (ACTRS) is proposed. The developed ACTRS uses a parabolic main reflector to obtain a plane wave at a short distance. Compared to the traditional underwater acoustic test system, the space distance is effectively compacted and the conversion process is reduced. Moreover, as the main device in the proposed ACTRS, the air-cavity with resin honeycomb structure was selected as the basic unit cell of the main reflector for the good underwater acoustic reflection performance. In addition, the edge sawtooth structure was selected to reduce the interference of edge diffraction in the quiet zone. Subsequently, the main reflector was simulated, trial-produced and measured. The measurement result shows good agreement with the simulation result. Finally, based on the proposed main reflector, the ACRTS was constructed for the object scattering and transducer directivity measurements. The test results were consistent with the simulation and the manufacturer’s manual data. Overall, the designed ACTRS can be used for large-scale target scattering and transducer directivity testing, providing a new reference for exploration of acoustic measurement methods. © 2022, The Authors. All rights reserved.

关键词： Underwater acoustics

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A Sequence-Scheduled and Query-Based MAC Protocol for Underwater Acoustic Networks with a Mobile Node

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Journal of Communications and Information Networks 2020年第2期5卷 150-159页

作者： Jing Huang Cheng Chi Wei Wang Haining Huang Institute of Acoustics Chinese Academy of SciencesBeijing 100190China Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

Since mobile nodes such as autonomous underwater vehicles can effectively expand network coverage,underwater acoustic networks with mobile nodes have attracted more and more attention in recent *** ensure the timely access of a mobile node without disturbing the normal transmission of data packets from static nodes,a sequence-scheduled and query-based medium access control protocol is proposed in this *** underwater nodes with data packets to be transmitted reply with a control packet for channel reservation after receiving the broadcast control packet of the buoy,then the reserved nodes transmit their data packets as the order calculated by the *** develop a mechanism to adjust the transmission order of the control packets sent by the underwater nodes in the handshake phase to reduce the collision and guarantee the success rate of reservation,and a query is initiated when the reserved control packet of the mobile node is not received by the buoy in the handshake to respond to the data transmission request of the mobile node in *** show that the maximum nodal throughput of the proposed MAC protocol increases by at least 20%and the access delay of the mobile node decreases by about 90%,compared to the two reference ***,the average access probability of the mobile node in the proposed protocol is more than 90%.

关键词： sequence-scheduled query underwater acoustic networks mobile nodes MAC protocol

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Controlling auto-focusing chirped perfect Laguerre-Gaussian beam to mitigate crosstalk in atmospheric turbulence

引用

Optical and Quantum Electronics 2025年第4期57卷 1-11页

作者： Ma, Yangbin Wang, Xinguang Shen, Yangbo Zhao, Ben Wang, Le Zhao, Shengmei College of Science Nanjing University of Posts and Telecommunications Wenyuan Road Jiangsu Nanjing210023 China Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and Telecommunications Wenyuan Road Jiangsu Nanjing210023 China Portland Institute Nanjing University of Posts and Telecommunications Wenyuan Road Jiangsu Nanjing210023 China School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Wenyuan Road Jiangsu Nanjing210023 China Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications New model road Jiangsu Nanjing210003 China Nanjing University of Posts and Telecommunications New model road Jiangsu Nanjing210003 China National Laboratory of Solid State Microstructures Nanjing University Hankou Road Jiangsu Nanjing210093 China

Auto-focusing beams can effectively mitigate orbital angular momentum (OAM) crosstalk in atmospheric turbulence. In this paper, we focus on the effect of the chirp factor on the crosstalk mitigation of chirped perfect Laguerre-Gaussian beam (CPLGB) based on the propagation model of CPLGB. The results demonstrate that a positive first-order chirp factor can significantly promote the auto-focusing of CPLGB, and increasing it can effectively mitigate the intermodal crosstalk of OAM modes in atmospheric turbulence, whereas a positive second-order chirp factor has a relatively weak effect on them. By comparing with Bessel Gaussian beam, perfect Laguerre-Gaussian beam, and perfect optical vortex beam, the CPLGB shows superior turbulence resistance when transmitted in atmospheric turbulence. Our results will be useful for optimizing the performance of free-space optical (FSO) communication systems with CPLGBs. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Gaussian beams

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A Modified Omega-K Algorithm for Bistatic Forward-Looking SAR Data Imaging

A Modified Omega-K Algorithm for Bistatic Forward-Looking SA...

引用

IEEE International Conference on radar

作者： Tinghao Zhang Yachao Li Xuan Song Tao Zhang Chunfeng Wu Ziyue Sun National Laboratory of Radar Signal Processing Xidian University Xi'an China Chengdu Aerospace Science and Technology Microelectronics System Research Institute Chengdu China University of Exeter BEng Electronic Enginnering Cornwall UK

ISBN: (纸本)9781665468893

Accurate two dimension frequency spectrum (2D FS) with acceleration, two-way range coupling terms, and spatial variant Doppler parameters are main problems to be solved in translational variant bistatic forward-looking SAR (TV BFSAR) with curved trajectory. For these issues, a modified Omega-K imaging algorithm is derived in this paper. The maximum usage of 2D FS based on method of series reversion (MSR) is achieved by linear range cell migration correction and 2D FS is linearized in bistatic range by using high-order polynomial fitting. Then, a method of azimuth resampling is introduced to implement compensation of spatial variant Doppler parameters. And the small-aperture data is focused in the azimuth frequency domain to avoid azimuth aliasing without padding zeros. Finally, the raw bistatic SAR data verifies the effectiveness of the proposed method

关键词： TV Azimuth Frequency-domain analysis Fitting Two dimensional displays radar imaging Doppler radar

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