IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-30 DOI: 10.1109/JSEN.2026.3737217

Tong Hao;Mingyang Kong;Fan Zhang;Jiaxin Song;Jiahao Yang;Haigang Wang;Haojie Xu;Ruliang Xu;Qianyu Wang;Junsheng Liang

{"title":"A Pt-Ir10 Wire-Wound High-Temperature Strain Gauge for Strain Measurement Up to 1300 °C","authors":"Tong Hao;Mingyang Kong;Fan Zhang;Jiaxin Song;Jiahao Yang;Haigang Wang;Haojie Xu;Ruliang Xu;Qianyu Wang;Junsheng Liang","doi":"10.1109/JSEN.2026.3737217","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3737217","url":null,"abstract":"High-temperature strain measurement above <inline-formula> <tex-math>$1300~^{circ }$ </tex-math></inline-formula>C remains challenging because conventional thin-film strain gauges (TFSGs) suffer from oxidation, resistance drift, and long-term instability. Herein, a Pt-Ir10 wire-wound strain gauge was fabricated using a self-developed winding apparatus, and the strain-sensing performance was systematically characterized from room temperature to <inline-formula> <tex-math>$1300~^{circ }$ </tex-math></inline-formula>C. The sensor exhibited a room-temperature gauge factor (GF) of 2.12 and maintained a clear dynamic strain response at <inline-formula> <tex-math>$1300~^{circ }$ </tex-math></inline-formula>C. A 5-h dwell test at <inline-formula> <tex-math>$1300~^{circ }$ </tex-math></inline-formula>C showed an average resistance drift rate of 0.681%/h, and a continuous cyclic loading–unloading test at <inline-formula> <tex-math>$1300~^{circ }$ </tex-math></inline-formula>C for approximately 7 h (about 8000 cycles) was conducted without signal interruption or sensing failure. Under high-temperature conditions, the average GF at <inline-formula> <tex-math>$1300~^{circ }$ </tex-math></inline-formula>C was 1.01. In addition, the influence of grid number on high-temperature sensitivity was investigated. Under the geometric parameters and fabrication process adopted in this work, the five-grid structure exhibited the highest average GF among the investigated configurations. These results demonstrate the feasibility of the Pt-Ir10 wire-wound strain gauge for strain measurement in extreme high-temperature environments.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32219-32226"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Vision-Based Two-Stage Method for GNSS/INS Integrated Navigation During GNSS Outages GNSS中断时基于视觉的两阶段GNSS/INS组合导航方法

IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-15 DOI: 10.1109/JSEN.2026.3732198

Yuan Liao;Zhaozhong Zhang;Kewei Li;Zhiping Zhou

{"title":"A Vision-Based Two-Stage Method for GNSS/INS Integrated Navigation During GNSS Outages","authors":"Yuan Liao;Zhaozhong Zhang;Kewei Li;Zhiping Zhou","doi":"10.1109/JSEN.2026.3732198","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3732198","url":null,"abstract":"Global navigation satellite system/inertial navigation system (GNSS/INS) integrated navigation experiences substantial positioning error accumulation during GNSS outages due to rapid inertial error drift. Although deep learning methods can estimate forward velocity from inertial measurement unit (IMU) data to mitigate position errors, these methods typically exhibit limited generalization ability across diverse vehicle operating environments, resulting in inconsistent performance and accuracy degradation when deployed under different conditions. This limitation arises because IMU signal characteristics—including noise levels and spectral content—vary significantly with vehicle speed, while a single model must compromise between competing signal properties across different speed ranges, hindering its ability to learn robust representations. To address this, we proposed a vision-based two-stage method to enhance generalization capability. First, a vision module is designed to identify the vehicle’s speed range from camera image sequences, enabling speed-specific model selection (SMS). Subsequently, the corresponding Frequency-Time Integration Network (FTINet) is employed to predict forward velocity, where multiple FTINet models are pretrained on speed-specific data subsets to capture distinct IMU signal characteristics at different speed ranges. FTINet leverages a dual-branch architecture to fuse instantaneous temporal dynamics with spectral features extracted via short-time Fourier transform (STFT) for precise velocity prediction. Evaluation on the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago Dataset (KITTI) and UrbanNav datasets shows that the proposed method reduces both forward-velocity estimation error and position error compared to the baseline lightweight odometer network (LONet). The method maintains stable trajectory-tracking performance across varying GNSS outage durations, effectively mitigating inertial drift during GNSS outages.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33314-33330"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

News from Japan: Sumitomo Bakelite Develops a Heat-Dissipating Insulating Sheet with an Industry-Leading Thermal Conductivity 来自日本的消息：住友电木开发了一种具有行业领先导热性的散热隔热片

IF 2 4区工程技术

IEEE Electrical Insulation Magazine Pub Date : 2026-11-01 Epub Date: 2026-10-27 DOI: 10.1109/MEI.2026.11755670

Yoshimichi Ohki

引用次数: 0

All-Fabric Bioimpedance Sensor for Joint Motion Tracking 关节运动跟踪全织物生物阻抗传感器

IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-18 DOI: 10.1109/JSEN.2026.3733616

Evan D. Patamia;Coco Mullen;Trisha L. Andrew

{"title":"All-Fabric Bioimpedance Sensor for Joint Motion Tracking","authors":"Evan D. Patamia;Coco Mullen;Trisha L. Andrew","doi":"10.1109/JSEN.2026.3733616","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733616","url":null,"abstract":"The demand for ubiquitous health monitoring has driven a shift from rigid, obtrusive wearables to seamlessly integrated textile systems. However, current motion tracking solutions typically rely on either spatially limited vision-based methods or drift-prone inertial measurement units (IMUs), both of which struggle to balance accuracy with usability, comfort, and energy efficiency. Here, we present a straightforward yet underexplored method for joint kinematics tracking: an all-fabric bioimpedance sensor that measures tissue volume changes during joint articulation to enable absolute position sensing. The system employs stretchable embroidered electrodes, consisting of silver-coated nylon threads and cotton embroidery floss in a herringbone stitch pattern, integrated with a custom-formulated photoinitiated chemical vapor deposition (piCVD) hydrogel system that creates a mechanically robust, washable interface. Validation against optical tracking systems across four diverse participants demonstrates tracking accuracies of 2.3° for ankle and 4.9° for elbow joints, performance comparable to state-of-the-art absolute position sensing systems, with the piCVD hydrogel composite maintaining consistent electrical properties through 20 consecutive wear cycles. Our system achieves this accuracy using a minimal signal processing chain of second-order polynomial regression and FFT filtering, enabling real-time computation entirely on ultralow-power microcontrollers.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33411-33420"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Model-Based Electrical Approach for Multiparameter Assessment of Marine Lubricating Oil 基于模型的船舶润滑油多参数评估电学方法

IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-28 DOI: 10.1109/JSEN.2026.3736476

D. Mishra;S. Parveen;A. Baral;S. Chakravorti

{"title":"A Model-Based Electrical Approach for Multiparameter Assessment of Marine Lubricating Oil","authors":"D. Mishra;S. Parveen;A. Baral;S. Chakravorti","doi":"10.1109/JSEN.2026.3736476","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3736476","url":null,"abstract":"Lubricating oil in marine diesel engines undergoes severe thermal, oxidative, and contamination stresses, leading to significant changes in its physicochemical and electrical characteristics. This article presents a frequency-domain spectroscopy (FDS)-based electrical sensing methodology for simultaneous estimation of moisture content, viscosity, and total base number (TBN) of lubricating oil. The broadband electrical response is modeled using a dual-relaxation framework incorporating conductive effects, enabling extraction of physically meaningful parameters associated with different degradation mechanisms. In particular, the dispersion parameters <inline-formula> <tex-math>$alpha _{1}$ </tex-math></inline-formula> and <inline-formula> <tex-math>$alpha _{2}$ </tex-math></inline-formula> are correlated with moisture-related fast polarization behavior and slower oxidation-induced degradation, respectively. Experimental investigations are carried out using laboratory-prepared samples under controlled aging conditions, followed by validation using real in-service marine engine oil samples. The predicted values show good agreement with experimental measurements, with estimation errors below 10% for all considered parameters. The proposed sensing approach provides a rapid, nondestructive, and efficient technique for multiparameter oil assessment, demonstrating strong potential for intelligent oil sensing and real-time marine diagnostic applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33602-33611"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LEMF-YOLO: Lightweight Early Multimodal Fusion Network Based on Improvement YOLO in Autonomous Driving Scenario 自动驾驶场景下基于改进YOLO的轻型早期多模态融合网络LEMF-YOLO

IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-18 DOI: 10.1109/JSEN.2026.3733534

Huixin Qin;Xianwei Rong;Xiaoyan Yu

{"title":"LEMF-YOLO: Lightweight Early Multimodal Fusion Network Based on Improvement YOLO in Autonomous Driving Scenario","authors":"Huixin Qin;Xianwei Rong;Xiaoyan Yu","doi":"10.1109/JSEN.2026.3733534","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733534","url":null,"abstract":"Accurate environmental perception and robust object recognition are indispensable for autonomous vehicle functionality. However, current deep learning-based object detection methods face challenges due to large parameter sizes and high model complexity, posing significant challenges for deployment on resource-constrained platforms. Moreover, existing models predominantly focus on LiDAR point clouds, with insufficient dedicated applications for millimeter-wave radar point clouds. To address these limitations, this article proposes a lightweight early multimodal fusion network based on improved YOLO for autonomous driving scenarios (LEMF-YOLO), built upon YOLOv12n with 3.29 M parameters. The network integrates image and millimeter-wave radar point cloud data for object detection through early fusion and incorporates a spatial and channel synergistic attention (SCSA) mechanism to enhance spatial and channel feature focus while suppressing noise. In addition, the improved loss function and feature extraction modules enable accurate recognition of objects of varying sizes while maintaining model lightness. Experiments on the revised nuScenes dataset demonstrate that the proposed model achieves a mean average precision (mAP50) of 91.8% and mAP50:95 of 63.1%, and exhibits improved accuracy under certain adverse conditions (e.g., rainy and low-light nights) within the evaluated dataset. These results suggest that the model can balance detection accuracy and lightweight design through multimodal data fusion.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32591-32605"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward Automated Parking Lot As-Built Measurement: All-Factor Extraction and Coarse-to-Fine Reliable Vectorization via LiDAR-Visual Fusion 面向自动化停车场竣工测量：基于激光雷达-视觉融合的全因素提取和从粗到精的可靠矢量化

IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-22 DOI: 10.1109/JSEN.2026.3734493

Tangjun Yao;Shaoming Zhang;Baoxin Feng;Jianmei Wang

{"title":"Toward Automated Parking Lot As-Built Measurement: All-Factor Extraction and Coarse-to-Fine Reliable Vectorization via LiDAR-Visual Fusion","authors":"Tangjun Yao;Shaoming Zhang;Baoxin Feng;Jianmei Wang","doi":"10.1109/JSEN.2026.3734493","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3734493","url":null,"abstract":"LiDAR and camera fusion-based parking lot as-built measurement (PLAM) requires precise extraction and vectorization to obtain the geometric dimensions of parking slots and verify their consistency with design standards. However, existing methods face three challenges. First, single-modal methods are insufficient for PLAM. Concretely, vision-based methods lack reliable 3-D geometry, while LiDAR-based methods are sensitive to intensity noise and lack uncertainty evaluation. Second, tightly coupled LiDAR-camera fusion is affected by residual local geometric misalignment, which may degrade boundary extraction accuracy. Third, unlike autonomous vehicle parking (AVP), as-built measurements require all-factor extraction of complete boundaries and slot numbers. Consequently, we propose an integrated LiDAR-visual method for robust parking slot extraction and vectorization. Specifically, we design a hierarchical fusion strategy that combines visual semantics with LiDAR intensity to achieve all-factor extraction, including complete boundaries and parking slot numbers. Subsequently, our coarse-to-fine vectorization first detects parkline edges in intensity images and then optimizes their positions in the point cloud space. The resulting vectorized parklines are accompanied by uncertainty evaluation. Extensive experiments on our self-collected dataset demonstrate superior performance in extraction and vectorization compared to state-of-the-art methods.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33032-33050"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LiDAR Sensor-Based 3-D Surface Measurement and Volume Estimation for Coal-Silo Monitoring 基于激光雷达的煤仓监测三维表面测量与体积估计

IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-21 DOI: 10.1109/JSEN.2026.3733766

Zhenming Lv;Guifeng Wang;Weipeng Shi

{"title":"LiDAR Sensor-Based 3-D Surface Measurement and Volume Estimation for Coal-Silo Monitoring","authors":"Zhenming Lv;Guifeng Wang;Weipeng Shi","doi":"10.1109/JSEN.2026.3733766","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733766","url":null,"abstract":"Accurate estimation of the volume of bulk coal in storage silos is essential for inventory management and operational safety. However, LiDAR-based silo measurement remains challenging due to incomplete observations and geometric distortions caused by complex operating environments. This article presents an integrated LiDAR measurement framework that combines training-free geometric segmentation, deterministic time-conditioned residual restoration, confidence-guided projected constrained Delaunay triangulation (CDT), and triangular height-field volume integration. A controlled synthetic benchmark comprising sand, lump coal, and grains is constructed for repeatable evaluation, while real lump-coal experiments provide end-to-end validation of the complete measurement chain. The proposed framework achieves an overall Chamfer distance of <inline-formula> <tex-math>${1}.{117}{,}{,}times {,}{,}{10}^{-{2}}$ </tex-math></inline-formula> m<sup>2</sup>, and the proposed CDT achieves a surface root-mean-square error (RMSE) of 0.0624 m with a mean relative volume error of 2.53%, compared with 3.07% for projected Delaunay triangulation. For real lump coal, ten repeated measurements at each of five reference volumes from 2.5 to 12.5 dm<sup>3</sup> yield relative volume errors of 1.25%–1.75%, with an across-level mean of 1.58%. The optimized processing time is approximately 1.41 s/frame, excluding LiDAR acquisition and transmission. These results demonstrate the effectiveness of the proposed framework for LiDAR-based coal-silo surface measurement and volume estimation.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33538-33547"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parameter Estimation of Smoothly Nutation Cone--Cylinder Target Based on Second-Order Taylor Approximation in Monostatic Radar 基于二阶泰勒近似的单基地雷达光滑章动锥-圆柱目标参数估计

IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-09 DOI: 10.1109/JSEN.2026.3730236

Fu-Long Xu;Ying Luo;Hang Yuan;Kai-Ming Li

{"title":"Parameter Estimation of Smoothly Nutation Cone--Cylinder Target Based on Second-Order Taylor Approximation in Monostatic Radar","authors":"Fu-Long Xu;Ying Luo;Hang Yuan;Kai-Ming Li","doi":"10.1109/JSEN.2026.3730236","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3730236","url":null,"abstract":"During the midcourse phase, cone–cylinder targets experience nutation that results from the coupling of precession and wobble, whose micro-Doppler signatures are vital for target identification. Existing monostatic radar algorithms for micro-motion parameter extraction are designed for cone targets. Faced with complex sliding scattering mechanisms of cone–cylinder targets and severe nonlinear coupling caused by nutation, these methods fail to retrieve 3-D micro-motion parameters. To address this issue, a 3-D micro-motion parameter extraction method for nutation cone–cylinder targets under monostatic radar is proposed based on approximate solution by second-order Taylor expansion. A micro-motion echo model for smooth nutation cone–cylinder targets is given according to target attitude. Time–frequency differences are used to eliminate high-order coupling, and second-order Taylor expansion simplifies the time-varying precession modulation. The matching pursuit algorithm is applied to estimate cone and wobble frequency, and a trust-region (TR) algorithm is employed to fit frequency shift coefficients. A stepwise solution strategy is finally adopted to solve for the 3-D micro-motion parameters. Experiments using ideal micro-Doppler curves, time–frequency diagrams, and FEKO electromagnetic simulations verify the availability of the proposed method.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32692-32708"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-Split Charge-Layer Engineering for Enhanced Low-Bias Sensing Performance of InGaAs/InP SAGCM SPADs 提高InGaAs/InP SAGCM spad低偏置传感性能的双分裂电荷层工程

IF 4.5 2区综合性期刊

IEEE Sensors Journal Pub Date : 2026-11-01 Epub Date: 2026-09-21 DOI: 10.1109/JSEN.2026.3734158

Smita Srivastava;Vikash Sharma;Prabal Dweep Khanikar;Ankur Gupta;Samaresh Das

{"title":"Dual-Split Charge-Layer Engineering for Enhanced Low-Bias Sensing Performance of InGaAs/InP SAGCM SPADs","authors":"Smita Srivastava;Vikash Sharma;Prabal Dweep Khanikar;Ankur Gupta;Samaresh Das","doi":"10.1109/JSEN.2026.3734158","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3734158","url":null,"abstract":"High-performance 1550 nm single-photon sensors require a favorable balance between photon detection efficiency (PDE) and dark count rate (DCR). In this work, a dual-split charge-layer architecture is proposed to optimize the electric-field distribution while preserving the overall charge sheet density. The influence of charge-layer doping ratio (DR) and thickness redistribution on the electric-field distribution, avalanche triggering probability, PDE, DCR, and specific detectivity (D<inline-formula> <tex-math>${}^{ast } $ </tex-math></inline-formula>) is systematically investigated. The optimized structure employs a higher doped, thinner sublayer adjacent to the multiplication region and a lightly doped, thicker sublayer near the grading region. Compared with the conventional single-photon avalanche diode (SPAD), the proposed architecture exhibits an increase in both PDE and D<inline-formula> <tex-math>${}^{ast }$ </tex-math></inline-formula> at an excess bias of 2 V. Furthermore, a D<inline-formula> <tex-math>${}^{ast }$ </tex-math></inline-formula> of <inline-formula> <tex-math>$1.29times 10^{{13}}$ </tex-math></inline-formula> Jones is achieved with a relative improvement in D<inline-formula> <tex-math>${}^{ast }$ </tex-math></inline-formula> of 15%. These results demonstrate that dual-split charge-layer engineering provides an effective and fabrication-compatible strategy for enhancing the low-bias sensing performance of room-temperature, 1550 nm InGaAs/InP separate absorption, grading, charge, and multiplication (SAGCM) SPADs for light detection and ranging (LiDAR) and other low-light sensing applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32358-32364"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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