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Enhanced sensitivity via polarization switching in fiber-based quantum sensing

Physical Review Applied 2023年第4期20卷 044020-044020页

作者： Xiaorui Tan Hongjing Li Qi Song Binke Xia Tailong Xiao Shurong Wei Jingzheng Huang Guihua Zeng State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronic Information and Electrical Engineering Institute of Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai 200240 People’s Republic of China

Quantum sensing has performance advantages that far exceed classical sensing, where sensing with photons is one of the most useful branches, and fiberization is a significant development approach to achieve a broader range of applications. However, the birefringence effect in optical fibers can cause polarization drift, which severely reduces the sensitivity of measurement on weak signals and influences the development of quantum sensing. In order to solve this problem, we propose a scheme that builds four time-division-multiplexing channels in the system by switching the polarization states of different optical pulses, and achieves the effect of suppressing polarization drift by analyzing and integrating the effective information of the four polarization channels. Moreover, the sensitivity and linear dynamic range of the system can be adjusted by inserting a reference phase. We demonstrate the feasibility of the system via theoretical analysis, and the numerical simulation results show that the scheme can demodulate the signal well and improve the signal-to-noise ratio by 30 dB, even in the case of the signal of the direct demodulation method is drowned out by noise and completely distorted.

关键词： Quantum sensing Optical techniques

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Joint Beam Management and SLAM for mmWave Communication systems

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IEEE Transactions on Communications 2023年第10期71卷 6162-6179页

作者： Que, Hang Yang, Jie Wen, Chao-Kai Xia, Shuqiang Li, Xiao Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Zte Corporation Shenzhen518055 China State Key Laboratory of Mobile Network and Mobile Multimedia Shenzhen518055 China Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China

The millimeter-wave (mmWave) communication technology, which employs large-scale antenna arrays, enables inherent sensing capabilities. Simultaneous localization and mapping (SLAM) can utilize channel multipath angle estimates to realize integrated sensing and communication design in 6G communication systems. However, existing works have ignored the significant overhead required by the mmWave beam management when implementing SLAM with angle estimates. This study proposes a joint beam management and SLAM design that utilizes the strong coupling between the radio map and channel multipath for simultaneous beam management, localization, and mapping. In this approach, we first propose a hierarchical sweeping and sensing service design. The path angles are estimated in the hierarchical sweeping, enabling angle-based SLAM with the aid of an inertial measurement unit (IMU) to realize sensing service. Then, feature-aided tracking is proposed that utilizes prior angle information generated from the radio map and IMU. Finally, a switching module is introduced to enable flexible switching between hierarchical sweeping and feature-aided tracking. Simulations show that the proposed joint design can achieve sub-meter level localization and mapping accuracy (with an error © 1972-2012 IEEE.

关键词： Mapping

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Use Anchor-Free Based Object Detectors to Detect Surface Defects

Use Anchor-Free Based Object Detectors to Detect Surface Def...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Liu, Jiaxue Zhang, Chao Li, Jianjun College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014000 China Inner Mongolia Autonomous Region Key Laboratory of Intelligent Diagnosis and Control of Electromechanical Systems Baotou014010 China College of Information Engineering Inner Mongolia University of Science and Technology Baotou014000 China

ISBN: (纸本)9783031702341

Many anchor-based object detectors have limitations in the detection process because of the presence of anchors. Therefore, in recent years, many researchers have shifted their focus to designing anchor-free object detectors. In this paper, we initially employ several common anchor-free detectors (CenterNet, FCOS, YOLOX-S, and YOLOV8-S) to detect surface defects in the hot-rolled strip datasets from Northeastern University (NEU-DET). Following experimental comparisons, YOLOV8-S demonstrates the best detection performance (mAP is 78.04% and the FPS is 8.45). Secondly, we utilize transfer learning to mitigate the overfitting problem that large models can induce on small datasets. Finally, we conduct a large number of experimental comparisons to verify the effectiveness of the model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Transfer learning

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Path Planning and information Protection of Mobile Robots Based on Deceptive Reinforcement Learning 1

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23rd IFToMM China International Conference on Mechanism and Machine Science and Engineering, IFToMM CCMMS 2022

作者： Xu, Qingfeng Shi, Yingnan Wang, Junchao Miller, Tim Xu, Hangding Wang, Tianmu Lin, Hongbin Liu, Xin-Jun Nie, Zhenguo Ths State Key Laboratory of Tribology Department of Mechanical Engineering Tsinghua University Beijing100084 China Beijing Key Laboratory of Precision/Ultra-Precision Manufacturing Equipments and Control Tsinghua University Beijing100084 China School of Computing and Information Systems Melbourne School of Engineering University of Melbourne Melbourne3000 Australia School of Mathematics and Information Science Guangzhou University Guangzhou510006 China

ISBN: (数字)9789811993985

ISBN: (纸本)9789811993978

Mobile robots have been widely used in military and other fields. By observing the path of the mobile robot, it is easy to infer the destination of its path. However, in some special situations, the user of the mobile robot does not want to reveal its purpose information, such as carrying out military attacks, sneak reconnaissance missions, etc. In order to protect the mobile robot's path information from being leaked, we combine the reinforcement learning path planning method to propose a computationally efficient deceptive reinforcement learning mobile robot path planning method. The path planned by this method balances the path cost and the target deception weight, making it difficult for observers observing the mobile robot path to predict the real target of the mobile robot, while ensuring a lower path cost for the mobile robot. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mobile robots

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Robust superresolution computational imaging with diffuser-refined illumination

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Physical Review Applied 2023年第6期20卷 064002-064002页

作者： Xinliang Zhai Xiaoyan Wu Tailong Xiao Jianohng Shi Guihua Zeng State Key Laboratory of Advanced Optical Communication Systems and Networks Center for Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai 200240 China

Computational imaging allows image formation with single-pixel detectors that have no spatial resolution. It has wide-ranging potential applications in fields ranging from biomedical imaging to remote sensing. However, the practical applications of computational imaging are limited due to the high sampling ratio, weak robustness, and low resolution. In this paper, we propose a robust superresolution computational imaging scheme with diffuser-refined illumination and multibucket detection. To increase the reconstruction efficiency, a dual-stream neural network incorporated with a physical model is developed for this imaging scheme, which can reconstruct a high-resolution image in ultralow-sampling-ratio (1.56%) and ultrahigh-noise (4 dB) environments without any data for pretraining. The experimental results demonstrate that the proposed method can increase the spatial resolution by a factor of 2.59 with respect to the diffraction limit of the original imaging system. We also successfully apply this method to image a real biomedical sample and believe that this study provides a computational-imaging framework for complicated practical applications.

关键词： Imaging & optical processing Optical techniques Super-resolution techniques

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Model Predictive control for T-S Fuzzy Markovian Jump systems Using Dynamic Prediction Optimization

arXiv

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arXiv 2024年

作者： Zhang, Bin Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

In this paper, the model predictive control (MPC) problem is investigated for the constrained discrete-time Takagi-Sugeno fuzzy Markovian jump systems (FMJSs) under imperfect premise matching rules. To strike a balance between initial feasible region, control performance, and online computation burden, a set of mode-dependent state feedback fuzzy controllers within the frame of dynamic prediction optimizing (DPO)-MPC is delicately designed with the perturbation variables produced by the predictive dynamics. The DPO-MPC controllers are implemented via two stages: at the first stage, terminal constraints sets companied with feedback gain are obtained by solving a "min-max" problem;at the second stage, and a set of perturbations is designed felicitously to enlarge the feasible region. Here, dynamic feedback gains are designed for off-line using matrix factorization technique, while the dynamic controller state is determined for online over a moving horizon to gradually guide the system state from the initial feasible region to the terminal constraint set. Sufficient conditions are provided to rigorously ensure the recursive feasibility of the proposed DPO-MPC scheme and the mean-square stability of the underlying FMJS. Finally, the efficacy of the proposed methods is demonstrated through a robot arm system example. © 2024, CC BY.

关键词： Predictive control systems

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A Communication-Efficient Distributed Optimization Algorithm with Linear Convergence over Directed Graphs

A Communication-Efficient Distributed Optimization Algorithm...

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Asian control Conference

作者： Yuzhu Duan Ziwen Yang Shanying Zhu Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Ministry of Education of China Shanghai P. R. China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The Industrial Internet of Things (IIoT) is increasingly emerging as a novel paradigm for information exchange within industrial production environments. To facilitate the efficient operation of IIoT, there is an urgent requirement for communication-efficient methods to transmit extensive production data. This paper proposes a communication-efficient distributed optimization algorithm tailored for the strongly convex and smooth convex optimization problems over a directed graph. To encompass a broader class of compressors, the assumption of compressor is relaxed to contain both relative and absolute errors. To mitigate compression errors, we adopt differential compression technique and dynamic scaling factor in the algorithm. In particular, under this compression assumption, a non-uniform quantizer is introduced to enable finite-bit transmission over communication channels and an upper bound of the required bits with this quantizer is provided. Moreover, we prove the linear convergence of the proposed algorithm with compression, and numerical examples are provided to verify the performance of the proposed algorithm.

关键词： Upper bound Heuristic algorithms Directed graphs Production Compressors Convex functions Optimization

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SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds

arXiv

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arXiv 2024年

作者： Wang, Yanbo Zhao, Wentao Cao, Chuan Deng, Tianchen Wang, Jingchuan Chen, Weidong Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

Although LiDAR semantic segmentation advances rapidly, state-of-the-art methods often incorporate specifically designed inductive bias derived from benchmarks originating from mechanical spinning LiDAR. This can limit model generalizability to other kinds of LiDAR technologies and make hyperparameter tuning more complex. To tackle these issues, we propose a generalized framework to accommodate various types of LiDAR prevalent in the market by replacing window-attention with our sparse focal point modulation. Our SFPNet is capable of extracting multi-level contexts and dynamically aggregating them using a gate mechanism. By implementing a channel-wise information query, features that incorporate both local and global contexts are encoded. We also introduce a novel large-scale hybrid-solid LiDAR semantic segmentation dataset for robotic applications. SFPNet demonstrates competitive performance on conventional benchmarks derived from mechanical spinning LiDAR, while achieving state-of-the-art results on benchmark derived from solid-state LiDAR. Additionally, it outperforms existing methods on our novel dataset sourced from hybrid-solid LiDAR. Code and dataset are available at https://***/Cavendish518/SFPNet and https://***. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Robust continuous-variable quantum key distribution in the finite-size regime

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Photonics Research 2024年第11期12卷 2549-2558页

作者： YUEHAN XU TAO WANG XIAOJUAN LIAO YINGMING ZHOU PENG HUANG GUIHUA ZENG State Key Laboratory of Advanced Optical Communication Systems and Networks Center of Quantum Sensing and Information ProcessingShanghai Jiao Tong UniversityShanghai 200240China Shanghai Research Center for Quantum Sciences Shanghai 201315China Hefei National Laboratory Hefei 230088China Shanghai XT Quantech Co. Ltd.Shanghai 200241China

Quantum key distribution(QKD)has been proven to be theoretically unconditionally ***,any theoretical security proof relies on certain *** QKD,the assumption in the theoretical proof is that the security of the protocol is considered under the asymptotic case where Alice and Bob exchange an infinite number of *** the continuous-variable QKD(CV-QKD),the finite-size effect imposes higher requirements on block size and excess noise ***,the local local oscillator(LLO)CV-QKD system cannot be considered time-invariant under long blocks,especially in cases of environmental ***,we propose an LLO CV-QKD scheme with time-variant parameter estimation and *** first establish an LLO CV-QKD theoretical model under the temporal modes of continuous-mode ***,a robust method is used to compensate for arbitrary frequency shift and arbitrary phase drift in CV-QKD systems with longer blocks,which cannot be achieved under traditional time-invariant parameter ***,the digital signal processing method predicated on high-speed reference pilots can achieve a time complexity of O*** the experiment,the frequency shift is up to 89.05 MHz/s and phase drift is up to 3.036 Mrad/s using a piezoelectric transducer(PZT)to simulate the turbulences in the practical *** a signal-to-interference ratio(SIR)of−51.67 dB,we achieve a secret key rate(SKR)of 0.29 Mbits/s with an attenuation of 16 dB or a standard fiber of 80 *** work paves the way for future long-distance field-test experiments in the finite-size regime.

关键词： finite proof size

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Grain Depot Wearable Device Detection Model Based on YOLOv5

Grain Depot Wearable Device Detection Model Based on YOLOv5

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Intelligent Management and Software Engineering (IMSE), International Conference on

作者： Jianjun Wu Yimeng Lian Qing Wen Tong Then Yuhua Zhu Zhihui Li College of Information Science and Engineering Henan University of Technology Zhengzhou China Key Laboratory of Grain Information Processing and Control Henan University of Technology Zhengzhou China

Standardized wearing of helmets and ventilators is the focus of grain depot safety management, which can effectively prevent safety accidents such as falling objects hurting people and fumigation poisoning. This paper is based on the deep learning algorithm to detect the wearing specifications of grain depot operations. Firstly, collect images by simulating the operation scene of the grain depot, recording video frames on the spot, etc. Use Labellmag software to mark the personnel wearing and not wearing the device, and create the original data set; Then, a grain depot wear standard monitoring model based on YOLOv5 is constructed. Add CBAM Attention to improve the network’s attention to local and global features and the ability to extract small target location information. In the post-processing stage, DIOU-NMS is optimized as the screening scheme of the target boxes to reduce the rate of missed detection rate of adjacent targets. Through the contrast experiment, the results show that the improved model mAP(mean average precision) is increased from 92.6% to 93.9%, and finally the detection model meeting the detection accuracy and real-time requirements is obtained.

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