IET Signal Processing最新文献_第4页

Insulator Defect Recognition Based on Vision Big-Model Transfer Learning and Stochastic Configuration Network 基于视觉大模型迁移学习和随机配置网络的绝缘体缺陷识别技术

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-06-19 DOI: 10.1049/2024/4182652

Siyuan Liu, Yihua Ma, Zedong Zheng, Xinfu Pang, Bingyou Li

{"title":"Insulator Defect Recognition Based on Vision Big-Model Transfer Learning and Stochastic Configuration Network","authors":"Siyuan Liu, Yihua Ma, Zedong Zheng, Xinfu Pang, Bingyou Li","doi":"10.1049/2024/4182652","DOIUrl":"https://doi.org/10.1049/2024/4182652","url":null,"abstract":"<div>\u0000 <p>Insulator faults are an important factor in causing outages and accidents in power transmission lines. In response to problems related to inefficient insulator positioning, limited robustness of insulator defect feature extraction methods, and the scarcity of defective insulator samples leading to poor classifier generalization, a method for insulator defect detection and recognition based on vision big-model transfer learning and a stochastic configuration network (SCN) is proposed. First, data augmentation methods, such as Mosaic and Mixup, are employed to mitigate overfitting in the YOLOv7 network. Second, StyleGanv3 adversarial generative networks are used to augment the dataset of defective insulators, which enhances dataset diversity. Third, a vision big-model transfer learning method based on DINOv2 is introduced to extract features from insulator images. Finally, an SCN classifier is used to determine the status of insulators. Experimental results demonstrate that the applied data augmentation methods effectively mitigate overfitting. YOLOv7 accurately detects insulator positions, and the use of the DINOv2 feature extraction method increases the accuracy of insulator defect recognition by 28.6%. Compared with machine learning classification methods, the SCN classifier achieves the highest accuracy improvement of 17.4%. The proposed method effectively detects insulator positions and recognizes insulator defects.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/4182652","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141430162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Residual Neural Network for Direction-of-Arrival Estimation of Multiple Targets in Low SNR 用于在低信噪比条件下估计多目标到达方向的残差神经网络

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-06-14 DOI: 10.1049/2024/4599954

Yanhua Qin

引用次数: 0

Manual Acupuncture Manipulation Recognition Method via Interactive Fusion of Spatial Multiscale Motion Features 通过交互式融合空间多尺度运动特征的手动针灸操作识别方法

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-05-29 DOI: 10.1049/2024/2124139

Jiyu He, Chong Su, Jie Chen, Jinniu Li, Jingwen Yang, Cunzhi Liu

{"title":"Manual Acupuncture Manipulation Recognition Method via Interactive Fusion of Spatial Multiscale Motion Features","authors":"Jiyu He, Chong Su, Jie Chen, Jinniu Li, Jingwen Yang, Cunzhi Liu","doi":"10.1049/2024/2124139","DOIUrl":"https://doi.org/10.1049/2024/2124139","url":null,"abstract":"<div>\u0000 <p>Manual acupuncture manipulation (MAM) is essential in traditional Chinese medicine treatment. MAM action recognition is important for junior acupuncturists’ training and education; however, there are obvious personalized differences in hand gestures among expert acupuncturists for the same type of MAM. In addition, during the MAM operations, the magnitude and frequency of the expert acupuncturists’ hand shape and relative needle-holding finger position changes are tiny and fast, resulting in difficulties in observing MAM action details. Thus, we propose a Spatial Multiscale Interactive Fusion MAM Recognition Network to solve the difficulties in MAM recognition. First, this paper presents an optical flow-based hand motion contour global feature extraction method for acupuncture hand shape. Second, to explore the motion rule between the needle-holding fingers during the MAM operations, we design a quantitative description method of the relative motion of the needle-holding fingers: an “interactive attention module,” which achieves feature fusion and mines the correlation between different scales of MAM action features. Finally, the proposed MAM recognition method was validated by 20 acupuncturists from the Beijing University of Traditional Chinese Medicine and 10 from the Beijing Zhongguancun Hospital who participated in the MAM video signal collection. The proposed recognition method achieves the highest average validation accuracy of 95.3% and the highest test accuracy of 96.0% for four typical MAMs, proving its feasibility and effectiveness.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/2124139","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141246168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Infrared Small Target Detection Based on Density Peak Search and Local Features 基于密度峰搜索和局部特征的红外小目标探测

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-05-27 DOI: 10.1049/2024/6814362

Leihong Zhang, Hui Yang, Qinghe Zheng, Yiqiang Zhang, Dawei Zhang

{"title":"Infrared Small Target Detection Based on Density Peak Search and Local Features","authors":"Leihong Zhang, Hui Yang, Qinghe Zheng, Yiqiang Zhang, Dawei Zhang","doi":"10.1049/2024/6814362","DOIUrl":"https://doi.org/10.1049/2024/6814362","url":null,"abstract":"<div>\u0000 <p>The detection of small infrared targets is still a challenging task and efficient and accurate detection plays a key role in modern infrared search and tracking military applications. However, small infrared targets are difficult to detect due to their weak brightness, small size and lack of shape, structure, texture, and other information elements. In this paper, we propose a target detection method. First, to address the problem that the proximity of targets to high-brightness clutter leads to missed detection of candidate targets, a Gaussian differential filtering preprocessed image is used to suppress high-brightness clutter. Second, a density-peaked global search method is used to determine the location of candidate targets in the preprocessed image. We then use local contrast to the candidate target points to enhance the gradient features and suppress background clutter. The Facet model is used to compute multidirectional gradient features at each point. A new efficient surrounding symmetric region partitioning scheme is constructed to capture the gradient characteristics of targets of different sizes in eight directions, followed by weighting the candidate target gradient characteristics using the standard deviation of the symmetric region difference. Finally, an adaptive threshold segmentation method is used to extract small targets. Experimental results show that the method proposed in this paper has better detection accuracy and robustness compared with other detection methods.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/6814362","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141246078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CSL-SFNet for Cooperative Spectrum Sensing in Cognitive Satellite Network with GEO and LEO Satellites CSL-SFNet 用于使用 GEO 和 LEO 卫星的认知卫星网络中的合作频谱传感

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-04-29 DOI: 10.1049/2024/5897908

Kai Yang, Shengbo Hu, Xin Zhang, Tingting Yan, Manqin Zhu

{"title":"CSL-SFNet for Cooperative Spectrum Sensing in Cognitive Satellite Network with GEO and LEO Satellites","authors":"Kai Yang, Shengbo Hu, Xin Zhang, Tingting Yan, Manqin Zhu","doi":"10.1049/2024/5897908","DOIUrl":"https://doi.org/10.1049/2024/5897908","url":null,"abstract":"<div>\u0000 <p>In a cognitive satellite network (CSN) with GEO and LEO satellites, there is a large propagation losses between the sensing satellite and the ground station. The results of spectrum sensing from a single satellite may be inaccurate, which will create serious interference in the primary satellite system. Cooperative spectrum sensing (CSS) has become the key technology for solving the above problems in recent years. However, most of the current CSS techniques are model-driven. They are difficult to model and implement in CSNs since their detection performance is strongly dependent on an assumed statistical model. Thus, we propose a novel CSS scheme, which uses convolutional neural networks (CNNs), self-attention (SA) modules, long short-term memory networks (LSTMs), and soft fusion networks, called CSL-SFNet. This scheme combines the advantages of CNNs, SA modules, and LSTMs to extract the features of the input signals from the spatial and temporal domains. Additionally, the CSL-SFNet makes use of a novel soft fusion technique that improves detection performance while also considerably reducing communication overhead. The simulation results demonstrate that the proposed algorithm can achieve a detection probability of 90% when the signal-to-noise ratio is −20 dB; it has a shorter running time and always outperforms the other CSS algorithms.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/5897908","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141096283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Weighted Sum Secrecy Rate Optimization for Cooperative Double-IRS-Assisted Multiuser Network 双 IRS 辅助多用户合作网络的加权和保密率优化

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-04-20 DOI: 10.1049/2024/7768640

Shaochuan Yang, Kaizhi Huang, Hehao Niu, Yi Wang, Zheng Chu, Gaojie Chen, Zhen Li

{"title":"Weighted Sum Secrecy Rate Optimization for Cooperative Double-IRS-Assisted Multiuser Network","authors":"Shaochuan Yang, Kaizhi Huang, Hehao Niu, Yi Wang, Zheng Chu, Gaojie Chen, Zhen Li","doi":"10.1049/2024/7768640","DOIUrl":"10.1049/2024/7768640","url":null,"abstract":"<div>\u0000 <p>In this paper, we present a double-intelligent reflecting surfaces (IRS)-assisted multiuser secure system where the inter-IRS channel is considered. In particular, we maximize the weighted sum secrecy rate of the system by jointly optimizing the beamforming vector for transmitted signal and artificial noise at the base station (BS) and the cooperative phase shifts of two IRSs, under the constraints of transmission power at the BS and the unit-modulus phase shift of IRSs. To tackle the nonconvexity of the optimization problem, we first convert the objective function to its concave lower bound by utilizing a novel successive convex approximation technique, then solve the transformed problem iteratively by applying an alternating optimization method. The Lagrange dual method, Karush–Kuhn–Tucker conditions, and alternating direction method of multipliers are applied to develop a low-complexity solution for each subproblem. Finally, simulation results are provided to verify the advantages of the cooperative double-IRS scheme in comparison with the benchmark schemes.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/7768640","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140680602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CFA-Based Splicing Forgery Localization Method via Statistical Analysis 通过统计分析实现基于 CFA 的拼接伪造定位方法

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-04-16 DOI: 10.1049/2024/9929900

Lei Liu, Peng Sun, Yubo Lang, Jingjiao Li

{"title":"CFA-Based Splicing Forgery Localization Method via Statistical Analysis","authors":"Lei Liu, Peng Sun, Yubo Lang, Jingjiao Li","doi":"10.1049/2024/9929900","DOIUrl":"10.1049/2024/9929900","url":null,"abstract":"<div>\u0000 <p>The color filter array of the camera is an effective fingerprint for digital forensics. Most previous color filter array (CFA)-based forgery localization methods perform under the assumption that the interpolation algorithm is linear. However, interpolation algorithms commonly used in digital cameras are nonlinear, and their coefficients vary with content to enhance edge information. To avoid the impact of this impractical assumption, a CFA-based forgery localization method independent of linear assumption is proposed. The probability of an interpolated pixel value falling within the range of its neighboring acquired pixel values is computed. This probability serves as a means of discerning the presence and absence of CFA artifacts, as well as distinguishing between various interpolation techniques. Subsequently, curvature is employed in the analysis to select suitable features for generating the tampering probability map. Experimental results on the Columbia and Korus datasets indicate that the proposed method outperforms the state-of-the-art methods and is also more robust to various attacks, such as noise addition, Gaussian filtering, and JPEG compression with a quality factor of 90.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/9929900","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140698176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Robust Sidelobe Cancellation Algorithm Based on Beamforming Vector Norm Constraint 基于波束成形矢量规范约束的稳健侧叶消除算法

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-04-04 DOI: 10.1049/2024/7696638

Qing Wang, Huanding Qin, Kai Yang, Hao Wu, Fangmin He, Jin Meng

{"title":"A Robust Sidelobe Cancellation Algorithm Based on Beamforming Vector Norm Constraint","authors":"Qing Wang, Huanding Qin, Kai Yang, Hao Wu, Fangmin He, Jin Meng","doi":"10.1049/2024/7696638","DOIUrl":"10.1049/2024/7696638","url":null,"abstract":"<div>\u0000 <p>Sidelobe cancellation (SLC) is a well-established beamforming technique for mitigating interference, particularly in the context of satellite communication (SATCOM). However, traditional SLC suffers from the issue of partially canceling the desired signal at high signal-to-noise ratio (SNR), primarily due to unconstrained beamforming processing. Extensive research has been conducted to address this problem; however, existing algorithms have limitations such as dependence on knowledge of signal array vectors or number of interferers and involve high computational complexity. In this paper, we propose a robust SLC algorithm based on beamforming vector norm constraint. Our proposal offers a practical solution by only requiring knowledge of the earth station antenna gain and maximum auxiliary array gain to the desired signal, both of which are fully known. Furthermore, compared to traditional SLC, our proposed method introduces additional computational complexity that only scales linearly with the size of the auxiliary array. Simulation results demonstrate comparable performance between our proposed method and existing techniques such as diagonal loading and spatial degrees-of-freedom control-based algorithms.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/7696638","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140741261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Critical Design Considerations on Continuous Frequency Modulation Localization Systems 连续调频定位系统的关键设计考虑因素

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-04-04 DOI: 10.1049/2024/6664937

Belal Al-Qudsi, Mohammed El-Shennawy, Niko Joram, Marco Gunia, Frank Ellinger

{"title":"Critical Design Considerations on Continuous Frequency Modulation Localization Systems","authors":"Belal Al-Qudsi, Mohammed El-Shennawy, Niko Joram, Marco Gunia, Frank Ellinger","doi":"10.1049/2024/6664937","DOIUrl":"https://doi.org/10.1049/2024/6664937","url":null,"abstract":"<div>\u0000 <p>Real-time locating systems (RTLSs) suffer from clock synchronization inaccuracy among their distributed reference nodes. Conventional systems require periodic time synchronization and typically necessitate a two-way ranging (TWR) clock synchronization protocol to eliminate their measurement errors. Particularly, frequency-modulated continuous-wave (FMCW) time-based location systems pose unique design considerations on the TWR that have a significant impact on the quality of their measurements. In this paper, a valid operation design diagram is proposed for the case of an FMCW time-based TWR synchronization protocol. The proposed diagram represents an intersection area of two boundary curves that indicate the functionality of the system at a given frequency bandwidth, spectral length, and clock synchronization ambiguity. It presents an intuitive illustration of the measurement’s expected accuracy by indicating a larger intersection area for relaxed design conditions and vice versa. Furthermore, the absence of a working condition can easily be detected before proceeding with the actual system development. To demonstrate the feasibility of the proposed diagram, four scenarios with different design constraints were evaluated in a Monte-Carlo model of a basic TWR system. Moreover, an experimental measurement setup demonstrated the validity of the proposed diagram. Both the simulation and experimental outcomes show that the indicated valid conditions and the distribution of the measurements’ accuracy are in very good agreement.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/6664937","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141096406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Industrial Wireless Communication Security Using Deep Learning Architecture-Based Channel Frequency Response 利用基于深度学习架构的信道频率响应增强工业无线通信安全性

IF 1.7 4区工程技术

IET Signal Processing Pub Date : 2024-03-28 DOI: 10.1049/2024/8884688

Lamia Alhoraibi, Daniyal Alghazzawi, Reemah Alhebshi, Liqaa F. Nawaf, Fiona Carroll

{"title":"Enhancing Industrial Wireless Communication Security Using Deep Learning Architecture-Based Channel Frequency Response","authors":"Lamia Alhoraibi, Daniyal Alghazzawi, Reemah Alhebshi, Liqaa F. Nawaf, Fiona Carroll","doi":"10.1049/2024/8884688","DOIUrl":"10.1049/2024/8884688","url":null,"abstract":"<div>\u0000 <p>Wireless communication plays a crucial role in the automation process in the industrial environment. However, the open nature of wireless communication renders industrial wireless sensor networks susceptible to malicious attacks that impersonate authorized nodes. The heterogeneity of the wireless transmission channel, coupled with hardware and software limitations, further complicates the issue of secure authentication. This form of communication urgently requires a lightweight authentication technique characterized by low complexity and high security, as inadequately secure communication could jeopardize the evolution of industrial devices. These requirements are met through the introduction of physical layer authentication. This article proposes novel deep learning (DL) models designed to enhance physical layer authentication by autonomously learning from the frequency domain without relying on expert features. Experimental results demonstrate the effectiveness of the proposed models, showcasing a significant enhancement in authentication accuracy. Furthermore, the study explores the efficacy of various DL architecture settings and traditional machine learning approaches through a comprehensive comparative analysis.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/8884688","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140370967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0