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Fast GNSS Acquisition Algorithm Based on SFFT with High Noise Immunity

China Communications 2023年第5期20卷 70-83页

作者： Haoran Zhang Ying Xu Ruidan Luo Yi Mao Aerospace Information Research Institute Chinese Academy of SceiencesBeijing 100094China School of Optoelectronics Univeristy of Chinese Academy of SceiencesBeijing 100049China State Key Laboratory of Air Traffic Management System and Technology Nanjing 210007China

The Global Navigation Satellite system(GNSS)has been widely used in various *** achieve positioning,the receiver must first lock the satellite *** is a complicated and expensive process that consumes a lot of resources of the *** this reason,this paper proposes a new fast acquisition algorithm with High Signal-tonoise ratio(SNR)performance based on sparse fast Fourier transform(HSFFT).The algorithm first replaces the IFFT process of the traditional parallel code phase capture algorithm with inverse sparse fast Fourier transform(ISFFT)with better computing performance,and then uses linear search combined with code phase discrimination to replace the positioning loop and the estimation loop with poor noise immunity in *** analysis and simulation results show that,compared with the existing SFFT parallel code phase capture algorithm,the calculation amount of this algorithm is reduced by 19%,and the SNR performance is improved by about *** with the classic FFT parallel code phase capture algorithm,the calculation amount of the algorithm in this paper is reduced by 43%,and when the capture probability is greater than 95%,the SNR performance of the two is approximately the same.

关键词： fast capture SNR sparse fast Fourier transform HashMap

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A SHIP DETECTION METHOD BASED ON YOLOV7 IN RANGE-COMPRESSED SAR DATA

A SHIP DETECTION METHOD BASED ON YOLOV7 IN RANGE-COMPRESSED ...

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IET International Radar Conference 2023, IRC 2023

作者： Tan, Xiangdong Leng, Xiangguang Wang, Jin Ji, Kefeng State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology National University of Defense Technology Changsha China

ISBN: (纸本)9781839539954

Synthetic Aperture Radar (SAR) is an exceptionally effective imaging technology capable of acquiring ground information regardless of weather conditions and time of day. SAR finds extensive applications in target detection, tracking, and recognition. Despite its wide imaging coverage and high resolution, ship target detection images face several challenges. The most prominent challenge is that both traditional methods such as constant false alarm rate (CFAR) detection and deep neural network methods require complex and time-consuming imaging processing, including but not limited to range migration correction and pulse compression processes. Consequently, real-time detection becomes arduous, leading to delayed results for subsequent applications such as target monitoring and tracking. To address this issue, this study proposes a novel ship detection method that leverages deep learning techniques along with range-compressed data from SAR images to enhance immediate target perception with a convolutional neural network algorithm. The aim is to improve the accuracy and timeliness of ship detection tasks. Given the limited availability of literature on this subject matter, this paper aims to provide an analysis of the proposed method's effectiveness through experimental results while also discussing future prospects. © The Institution of Engineering & technology 2023.

关键词： Convolutional neural networks

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Oil‐paper insulation partial discharge ultrasonic multifrequency sensing array based on fibre‐optic Fabry-Perot sensor

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High Voltage 2022年第2期7卷 325-335页

作者： Zhixian Zhang Jiali Lei Weigen Chen Tianhe Yang Yuxuan Song Kejie Wu Fan Liu State Key Laboratory of Power Transmission Equipment&System Security and New Technology Chongqing UniversityChongqingChina State Grid Hubei Electric Power Research Institute WuhanHubeiChina

In order to improve the sensitivity and accuracy of oil‐paper insulation partial discharge detection by the fibre‐optic Fabry-Perot(FP)ultrasonic sensor,this work studied the ultrasonic signal’s frequency characteristics of typical oil‐paper insulation partial dis-charges and the vibration characteristics of the FP sensor’s diaphragm in the liquid *** on the works above,a multifrequency FP sensor array is proposed,consisting of several FP sensors with different resonant frequencies to detect partial *** experimental results show that the liquid environment has a significant effect on the vibration characteristics of the FP sensor’s diaphragm,and the sensitivity and accuracy of partial discharge detection can be improved based on the multifrequency FP sensing array,which can also be applied in the pattern recognition and localisation of partial discharges.

关键词： insulation fibre sensor

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Flexible Sensors Used for Lower Assisting Exoskeleton 16th

Flexible Sensors Used for Lower Assisting Exoskeleton

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Xiao, Yang Chen, Chunjie Liu, Yao Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9789819964857

In recent years, with the aging of the social population, exoskeleton robots have a wide range of application prospects in rehabilitation assistance, walking assistance, and physical expansion. However, the sensors developed for traditional robots currently have problems such as poor wearability, poor biocompatibility, and poor adaptability. To realize human-machine motion coordination assistance with multiple degrees of freedom and multiple motion states more effectively, and improve the flexibility, real-time performance, and reliability of the interaction between the wearer and the exoskeleton, it is necessary to design a set of flexible sensing systems to monitor the wearer’s motion status. It provides intelligent sensing technology support for adaptive control of exoskeleton in complex environments. This paper proposes a new flexible stretchable capacitive sensor and introduces its selection and manufacturing process. In the following experiments, three different slopes in the static experiment and dynamic experiment were used to test its performance and explore the accuracy and stability of its angle measurement. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Capacitive sensors

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Granular Ionogel Particle Inks for 3D Printed Tough and Stretchable Ionotronics

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Research 2024年第1期2023卷 429-442页

作者： Yuan Yao Yue Hui Zhenhua Wang Hehao Chen Heng Zhu Nanjia Zhou Key Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of EngineeringWestlake UniversityHangzhou 310024Zhejiang ProvinceChina Institute of Advanced Technology Westlake Institute for Advanced StudyHangzhou 310024Zhejiang ProvinceChina School of Chemical Engineering and Advanced Materials the University of AdelaideAdelaide 5005South AustraliaAustralia State Key Laboratory of Fluid Power&Mechatronic System Key Laboratory of Soft Machines and Smart Devices of Zhejiang ProvinceCenter for X-MechanicsDepartment of Engineering MechanicsZhejiang UniversityHangzhou 310027China

Ionogels have garnered great attention as promising soft conducting materials for the fabrication of flexible energy storage devices,soft actuators,and ***,the leakage of the ionic liquids,weak mechanical strength,and poor manufacturability have greatly limited their reliability and ***,we propose a new ionogel synthesis strategy by utilizing granular zwitterionic microparticles to stabilize ionic *** ionic liquids swell the microparticles and physically crosslink microparticles via either electronic interaction or hydrogen *** introducing a photocurable acrylic monomer enables the fabrication of double-network(DN)ionogels with high stretchability(>600%)and ultrahigh toughness(fracture energy>10 kJ/m^(2)).The synthesized ionogels exhibit a wide working temperature of−60 to 90℃.By tuning the crosslinking density of microparticles and physical crosslinking strength of ionogels,we synthesize DN ionogel inks and print them into three-dimensional(3D)*** ionogelbased ionotronics are 3D printed as demonstrations,including strain gauges,humidity sensors,and ionic skins made of capacitive touch sensor *** covalently linking ionogels with silicone elastomers,we integrate the ionogel sensors onto pneumatic soft actuators and demonstrate their capacities in sensing large *** our last demonstration,multimaterial direct ink writing is harnessed to fabricate highly stretchable and durable alternating-current electroluminescent devices with arbitrary *** printable granular ionogel ink represents a versatile platform for the future manufacturing of ionotronics.

关键词： crosslinking utilizing gauge

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Curing curve prediction using genetic algorithm optimized back propagation neural network 9

Curing curve prediction using genetic algorithm optimized ba...

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2023 9th International Forum on Manufacturing technology and Engineering Materials, ICMTEM 2023

作者： Zhang, Ruming Guan, Kunpeng Wu, Chenchen Shenyang University of Technology Shenyang110870 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Science and Technology Liaoning Anshan114051 China

Thermoset composites constructed with monolithic moulding can significantly reduce the number of parts and connectors, improve the reliability of the composite structure, and reduce production costs. For such composite components, the degree-of-cure (DoC) curve is normally considered to evaluate the curing process, so that the curing process-induced deformation and residual stress can meet the manufacturing requirements. In this paper, a method is proposed to predict the DoC curve based on the neural network. First, the DoC curves for AS4/3501-6 composite structures were obtained from ABAQUS and HETVAL subroutine, and the results were verified by published values. Next, the curves of temperature over time and DoC over time were generated to train the neural network. Finally, the back propagation (BP) neural network is optimized using the genetic algorithm (GA), and the DoC curve prediction model is created. The results demonstrate that, with a maximum error of 3.24%, the simulated curves essentially correspond with published values. Evaluation and validation analyses show that the prediction of the DoC curve using the GA-BP neural network yields high computational efficiency and accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Genetic algorithms

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WaveDN: A Wavelet-based Training-free Zero-shot Enhancement for Vision-Language Models 24

WaveDN: A Wavelet-based Training-free Zero-shot Enhancement ...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Li, Jiulin Yang, Mengyu Tian, Ye Zhang, Lanshan Lu, Yongchun Liu, Jice Wang, Wendong State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System and Network Culture Beijing China School of Computer Science Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798400706868

Vision-Language Models (VLMs) built on contrastive learning, such as CLIP, demonstrate great transferability and excel in downstream tasks like zero-shot classification and retrieval. To further enhance the performance of VLMs, existing methods have introduced additional parameter modules or fine-tuned VLMs on downstream datasets. However, these methods often fall short in scenarios where labeled data for downstream tasks is either unavailable or insufficient for fine-tuning, and the training of additional parameter modules may considerably impair the existing transferability of VLMs on open-set tasks. To alleviate this issue, we introduce WaveDN, a wavelet-based distribution normalization method that can boost the VLMs' performance on downstream tasks without parametric modules or labeled data. Initially, wavelet distributions are extracted from the embeddings of the sampled, unlabeled test samples. Subsequently, WaveDN conducts a hierarchical normalization across the wavelet coefficients of all embeddings, thereby incorporating the distributional characteristics of the test data. Finally, the normalized embeddings are reconstructed via inverse wavelet transformation, facilitating the computation of similarity metrics between the samples. Through extensive experiments on two downstream tasks, using a total of 14 datasets covering text-image and text-audio modal data, WaveDN has demonstrated superiority compared to state-of-the-art methods. © 2024 ACM.

关键词： Visual languages

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Performance analysis of the tight combination of GPS, BDS, GALILEO, and QzsS mixed frequencies signals

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Geodesy and Geodynamics 2024年第4期15卷 366-378页

作者： Yu Han Fangjun Qin Xugang Lian Shengliang Wang Leiyuan Qian Wenhua Huang College of Electrical Engineering Naval University of EngineeringWuhan 430033China College of Mining Engineering Taiyuan University of TechnologyTaiyuan 030024China State Key Laboratory of Satellite Navigation System and Equipment Technology Shijiazhuang 050081China State Key Laboratoryof Geodesy and Earth'sDynamics Innovation AcademyforPrecision Measurement Scienceand Technology Chinese Academy of SciencesWuhan 430077China China Energy Engineering Group Shanxi Electric Power Engineering CO.LTD. Taiyuan 030001China

With the gradual development and modernization of satellite navigation systems,using observation information from multi-GNss has become one of the hot-spot issues in recent ***-system loose combinations form double-difference observation equations within their respective systems,and the positioning effect is ***,the interchangeability and compatible interoperability between global navigation satellite systems(GNSS)cannot be truly *** the same time,when the number of visible satellites decreases abruptly,the positioning performance deteriorates *** paper focuses on the GNsS multi-system tight combination relative positioning technique,gives a mathe-matical model of multi-system tight combination relative positioning considering differential inter-system bias(DISB),and analyzes the time-varying characteristics of DISB at overlapping and non-overlapping frequencies among GPS/Galileo,GPS/BDS,and GPS/QZSS in terms of receiver brand,tem-perature,and receiver *** GNsS tight combination relative positioning performance is verified by static data from Curtin University and dynamic data measured at Taiyuan University of *** results show that compared with loose combination,the ambiguity-fixed rate increases from 62.18%to 97.60%for static data and from 74.97%to 99.53%for dynamic data when the elevation mask angle is 50°,resulting in a significant improvement in positioning performance.

关键词： GNSS Mix frequencies Redundancy Tightcombination Differential inter-system bias

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Thick-Mask Model based on multi-channel U-Net for EUV Lithography 2

Thick-Mask Model based on multi-channel U-Net for EUV Lithog...

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DTCO and Computational Patterning II 2023

作者： Yu, Chengzhen Ma, Xu Key Laboratory of Photoelectronic Imaging Technology System of Ministry of Education of China School of Optics and Photonics Beijing Institute of Technology Beijing100081 China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781510660977

Mask three-dimensional (M3D) effects are non-negligible for imaging simulation of EUV lithography systems. Especially, the curvilinear mask obtained by inverse lithography technique (ILT) increases the difficulty to calculate the diffraction spectrum of the thick masks. In this paper, a fast thick-mask model based on multi-channel U-Net (MCU-Net) is proposed to solve this problem. The diffraction near-field (DNF) of thick mask in EUV lithography is characterized by four complex-valued diffraction matrices, the real parts and imagery parts of which can be represented by eight real-valued diffraction matrices in total. Then, all of the eight real-valued diffraction matrices can be synthesized together using the proposed MCU-Net model. The parameters of MCU-Net are trained in a supervised manner based on a precalculated DNF dataset of curvilinear thick masks. The comparison of the proposed method with some other learning-based thick-mask models is provided and discussed. It shows that the MCU-Net is efficient and accurate to simulation the M3D effect in EUV lithography. © 2023 SPIE.

关键词： Diffraction

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Source Separation of Piano Concertos Using Hybrid LSTM-Transformer Model

Source Separation of Piano Concertos Using Hybrid LSTM-Trans...

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2024 International Conference on Culture-Oriented Science and technology, CoST 2024

作者： Liu, JingYu He, Wei Zhou, Jingjing Jiang, Wei State Key Laboratory of Media Convergence and Communication Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (纸本)9798350380347

Music source separation, the process of extracting independent audio streams from a complex mix, has traditionally focused on isolating vocals, drums, bass, and other primary sources. This study tackles the more intricate task of separating the piano component from a piano concerto-a challenge compounded by the diverse range of instruments and the dynamic shifts in volume and timbre. Unlike traditional music separation tasks, the piano's distinct characteristics and its interaction with the orchestra demand a more nuanced *** address the scarcity of multi-track recordings for piano concertos, this research pioneers an artificial data synthesis strategy to create a robust training dataset. We introduce a novel hybrid deep learning model that integrates Long Short-Term Memory (LSTM) networks with Transformer architecture, capitalizing on their complementary strengths to distinguish piano melodies from the rich tapestry of orchestral sounds. Our experiments demonstrate that this hybrid approach significantly outperforms conventional methods, with an improvement of 3.18 dB in signal-to-distortion ratio. These results not only validate the efficacy of proposed method but also pave the way for innovative applications in classical music source separation. © 2024 IEEE.

关键词： Source separation

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