Pub Date : 2025-03-14DOI: 10.1109/JSEN.2025.3548849
Buhong Zhang;Meibo Lv;Zhigang Wang;Xiaodong Liu;Wuwei Wang
Sea-sky line detection (SSLD) is pivotal for applications such as unmanned surface vehicles (USVs) navigation and maritime target detection. However, existing algorithms are susceptible to interference from adverse weather, illumination change, and the presence of waves, leading to poor detection accuracy and robustness. To address these challenges, we propose a novel SSLD algorithm based on a deep semantic segmentation network. First, we integrate the strengths of convolutional neural networks (CNNs) and Transformers in a lightweight block named efficient vision transformer (E-ViT). This block enables efficient interaction and aggregation of local and global features with lower computational overhead. Building upon E-ViT, we develop an encoder module that significantly improves the accuracy of semantic segmentation while maintaining the network’s lightweight. Then, we design a robust postprocessing module, which leverages semantic information to effectively remove interferences and filter out candidate points for the sea-sky line, thereby achieving high-precision SSLD. Finally, we construct a well-labeled maritime scene dataset with diverse complex attributes to validate the proposed algorithm. Experimental results demonstrate that our method outperforms several state-of-the-art algorithms in terms of both accuracy and robustness in complex maritime scenarios.
{"title":"Robust Sea-Sky Line Detection in Complex Maritime Environments via Semantic Segmentation","authors":"Buhong Zhang;Meibo Lv;Zhigang Wang;Xiaodong Liu;Wuwei Wang","doi":"10.1109/JSEN.2025.3548849","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3548849","url":null,"abstract":"Sea-sky line detection (SSLD) is pivotal for applications such as unmanned surface vehicles (USVs) navigation and maritime target detection. However, existing algorithms are susceptible to interference from adverse weather, illumination change, and the presence of waves, leading to poor detection accuracy and robustness. To address these challenges, we propose a novel SSLD algorithm based on a deep semantic segmentation network. First, we integrate the strengths of convolutional neural networks (CNNs) and Transformers in a lightweight block named efficient vision transformer (E-ViT). This block enables efficient interaction and aggregation of local and global features with lower computational overhead. Building upon E-ViT, we develop an encoder module that significantly improves the accuracy of semantic segmentation while maintaining the network’s lightweight. Then, we design a robust postprocessing module, which leverages semantic information to effectively remove interferences and filter out candidate points for the sea-sky line, thereby achieving high-precision SSLD. Finally, we construct a well-labeled maritime scene dataset with diverse complex attributes to validate the proposed algorithm. Experimental results demonstrate that our method outperforms several state-of-the-art algorithms in terms of both accuracy and robustness in complex maritime scenarios.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"14453-14464"},"PeriodicalIF":4.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840112","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}
Pub Date : 2025-03-13DOI: 10.1109/JSEN.2025.3548725
Huahuang Luo;Yuan Wang;Xiaoyi Wang;Yi-Kuen Lee;Qingqing Ke
This article presents the development of highly sensitive micro thermal expansion-based angular motion (TEAM) sensors utilizing water and ethanol as the working fluids. Theoretical analysis demonstrates that replacing the gas medium with liquids significantly increases the sensitivity of TEAM sensors, attributed to the larger Rayleigh number (Ra*). Among the two liquids studied, the ethanol-based TEAM sensor exhibits greater sensitivity to fluctuations in thermal properties than the water-based sensor. To ensure waterproofing, a Parylene-C coating was applied as the encapsulation layer for developing the novel liquid-based sensors. Experimental results identify a critical Ra* of 2950, which distinguishes the linear and nonlinear regions of operation for both the water-based and ethanol-based sensors. In the linear region, the water-based and ethanol-based sensors exhibit normalized sensitivities of 0.1638 and 0.37 mV/°/s/mW, respectively, which are more than 10 times and 20 times higher than those of conventional air-based sensors, supporting the theoretical predictions and confirming the feasibility of the proposed design strategy. Furthermore, the ethanol-based TEAM sensor outperforms the sulfur hexafluoride (SF6)-based sensor, currently the most sensitive gas-based thermal angular motion (TAM) sensor, by over five times. The experimental comparisons of single-heater and dual-heater configurations further highlight the importance of the dual-heater setup in minimizing heat loss and enhancing sensor performance, particularly for liquid-based sensors. These findings demonstrate the potential of the liquid-enhanced TEAM sensor for developing more accurate and reliable angular motion detection systems in complex environments.
{"title":"A Novel Liquid-Enhanced Micro Thermal Expansion-Based Angular Motion Sensor With Ultrahigh Sensitivity","authors":"Huahuang Luo;Yuan Wang;Xiaoyi Wang;Yi-Kuen Lee;Qingqing Ke","doi":"10.1109/JSEN.2025.3548725","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3548725","url":null,"abstract":"This article presents the development of highly sensitive micro thermal expansion-based angular motion (TEAM) sensors utilizing water and ethanol as the working fluids. Theoretical analysis demonstrates that replacing the gas medium with liquids significantly increases the sensitivity of TEAM sensors, attributed to the larger Rayleigh number (Ra*). Among the two liquids studied, the ethanol-based TEAM sensor exhibits greater sensitivity to fluctuations in thermal properties than the water-based sensor. To ensure waterproofing, a Parylene-C coating was applied as the encapsulation layer for developing the novel liquid-based sensors. Experimental results identify a critical Ra* of 2950, which distinguishes the linear and nonlinear regions of operation for both the water-based and ethanol-based sensors. In the linear region, the water-based and ethanol-based sensors exhibit normalized sensitivities of 0.1638 and 0.37 mV/°/s/mW, respectively, which are more than 10 times and 20 times higher than those of conventional air-based sensors, supporting the theoretical predictions and confirming the feasibility of the proposed design strategy. Furthermore, the ethanol-based TEAM sensor outperforms the sulfur hexafluoride (SF6)-based sensor, currently the most sensitive gas-based thermal angular motion (TAM) sensor, by over five times. The experimental comparisons of single-heater and dual-heater configurations further highlight the importance of the dual-heater setup in minimizing heat loss and enhancing sensor performance, particularly for liquid-based sensors. These findings demonstrate the potential of the liquid-enhanced TEAM sensor for developing more accurate and reliable angular motion detection systems in complex environments.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"12805-12812"},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143845526","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}
Pub Date : 2025-03-13DOI: 10.1109/JSEN.2025.3548899
László Lindenmaier;Balázs Czibere;Szilárd Aradi;Tamás Bécsi
Advanced driver assistance and autonomous systems require an enhanced perception system, fusing the data of multiple sensors. Many automotive sensors provide high-level data, such as tracked objects, i.e., tracks, usually fused in a track-to-track manner. The core of this fusion is the track-to-track association (T2TA), intending to create assignments between the tracks. In conventional T2TA, the assignment likelihood function is derived from “diffuse prior,” neglecting that the sensors may provide duplicated tracks of a target. Moreover, conventional association algorithms are usually computationally demanding due to the combinatorial nature of the problem. The first motivation of this work is to obtain a computationally efficient and robust solution, reflecting these problems. Another crucial element of track-to-track fusion is track management, which maintains the list of tracks by initializing and deleting tracks, thus having a great impact on the reliability of the fusion output. In this article, we propose a novel track-to-track fusion architecture in which the fused tracks are fed back to the association. The proposed method comprises two main contributions. First, a computationally efficient association algorithm is provided in which the “diffuse prior” is replaced with an informative prior, exploiting the feedback loop of the fused tracks. Moreover, it tackles duplicated tracks. Second, a track management system (TMS) relying on a revamped track existence probability fusion is proposed, contributing to efficient false track filtering and continuous object tracking. The proposed methodology is evaluated on real-world data of a frontal perception system. The results show that the proposed association outperforms the conventional methods; still, it maintains a favorable complexity, contributing to real-time applicability. The TMS relying on the revamped existence probability fusion can efficiently filter false tracks and continuously track objects. Moreover, the resulting overall track-to-track fusion outperforms the state-of-the-art multiobject tracking-based fusion algorithms.
{"title":"A Robust and Runtime-Efficient Track-to-Track Fusion for Automotive Perception Systems","authors":"László Lindenmaier;Balázs Czibere;Szilárd Aradi;Tamás Bécsi","doi":"10.1109/JSEN.2025.3548899","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3548899","url":null,"abstract":"Advanced driver assistance and autonomous systems require an enhanced perception system, fusing the data of multiple sensors. Many automotive sensors provide high-level data, such as tracked objects, i.e., tracks, usually fused in a track-to-track manner. The core of this fusion is the track-to-track association (T2TA), intending to create assignments between the tracks. In conventional T2TA, the assignment likelihood function is derived from “diffuse prior,” neglecting that the sensors may provide duplicated tracks of a target. Moreover, conventional association algorithms are usually computationally demanding due to the combinatorial nature of the problem. The first motivation of this work is to obtain a computationally efficient and robust solution, reflecting these problems. Another crucial element of track-to-track fusion is track management, which maintains the list of tracks by initializing and deleting tracks, thus having a great impact on the reliability of the fusion output. In this article, we propose a novel track-to-track fusion architecture in which the fused tracks are fed back to the association. The proposed method comprises two main contributions. First, a computationally efficient association algorithm is provided in which the “diffuse prior” is replaced with an informative prior, exploiting the feedback loop of the fused tracks. Moreover, it tackles duplicated tracks. Second, a track management system (TMS) relying on a revamped track existence probability fusion is proposed, contributing to efficient false track filtering and continuous object tracking. The proposed methodology is evaluated on real-world data of a frontal perception system. The results show that the proposed association outperforms the conventional methods; still, it maintains a favorable complexity, contributing to real-time applicability. The TMS relying on the revamped existence probability fusion can efficiently filter false tracks and continuously track objects. Moreover, the resulting overall track-to-track fusion outperforms the state-of-the-art multiobject tracking-based fusion algorithms.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"14022-14035"},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10925581","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose and experimentally demonstrate a chaotic Brillouin optical correlation-domain analysis (BOCDA) based on a differential correlation demodulation configuration. Multiple correlation peak (CP) localization is achieved by the gain of the central CP (CCP) and that of the difficult-to-eliminate time-delay signature (TDS) peak. The probe differential scheme is introduced and simulated to eliminate the influence of power superposition and obtain the optimized gain distribution. On this basis, the gain interval extraction method is proposed to separate the gain of CCP and TDS positions, and the corresponding Brillouin gain spectra are obtained in simulation and experiment. Ultimately, the synchronous localization of the CCP and TDS with a sensing distance of 410 m and a spatial resolution of less than 8 cm is experimentally demonstrated.
{"title":"Chaotic Brillouin Optical Correlation-Domain Analysis Based on Differential Correlation Demodulation","authors":"Haochen Huang;Yahui Wang;Lintao Niu;Jing Chen;Haokun Zhang;Mingjiang Zhang","doi":"10.1109/JSEN.2025.3548641","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3548641","url":null,"abstract":"We propose and experimentally demonstrate a chaotic Brillouin optical correlation-domain analysis (BOCDA) based on a differential correlation demodulation configuration. Multiple correlation peak (CP) localization is achieved by the gain of the central CP (CCP) and that of the difficult-to-eliminate time-delay signature (TDS) peak. The probe differential scheme is introduced and simulated to eliminate the influence of power superposition and obtain the optimized gain distribution. On this basis, the gain interval extraction method is proposed to separate the gain of CCP and TDS positions, and the corresponding Brillouin gain spectra are obtained in simulation and experiment. Ultimately, the synchronous localization of the CCP and TDS with a sensing distance of 410 m and a spatial resolution of less than 8 cm is experimentally demonstrated.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13033-13038"},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840070","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}
The advancement of hydrogel-based epidermal sensors that integrate multifunctionality, high transparency, rapid processing, and heightened sensitivity is of significant interest. Herein, we present an efficient approach for the fabrication of flexible dual-mode epidermal sensors through the ultraviolet (UV)-curing 3-D printing of polyacrylamide (PAM)-based ionic hydrogels. The hydrogel precursor incorporates sodium dodecyl sulfate (SDS) monomers to augment the water dispersibility of the 2,4,6-trimethylbenzoyl-diphenylphosphine oxide (TPO) photoinitiator, thereby substantially increasing the photocuring efficiency of the ionic hydrogel. As a result, the distinctive surface microstructures of PAM-based ionic hydrogels can be engineered for sensors with varying sensing modalities to improve detection performance. The piezoelectric tactile sensor, incorporating a concentric ring microstructure, demonstrates a sensitivity coefficient of $1.39~text {mV}cdot text { kPa}^{-{1}}$ . Conversely, the resistive strain sensor, characterized by a high-density reticular hollow structure, exhibits the highest gauge factor of 24.87. Furthermore, each sensor modality demonstrates excellent temporal response and stability, confirming its applicability in motion monitoring and Morse code transmission.
{"title":"3-D Printing of PAM Hydrogel-Based Iontronic for Dual-Mode Epidermal Sensors","authors":"Yue Zhang;Ao Lan;Yuanhao Xia;Xiangyu Yin;Bingwei He;Pengli Zhu","doi":"10.1109/JSEN.2025.3549188","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3549188","url":null,"abstract":"The advancement of hydrogel-based epidermal sensors that integrate multifunctionality, high transparency, rapid processing, and heightened sensitivity is of significant interest. Herein, we present an efficient approach for the fabrication of flexible dual-mode epidermal sensors through the ultraviolet (UV)-curing 3-D printing of polyacrylamide (PAM)-based ionic hydrogels. The hydrogel precursor incorporates sodium dodecyl sulfate (SDS) monomers to augment the water dispersibility of the 2,4,6-trimethylbenzoyl-diphenylphosphine oxide (TPO) photoinitiator, thereby substantially increasing the photocuring efficiency of the ionic hydrogel. As a result, the distinctive surface microstructures of PAM-based ionic hydrogels can be engineered for sensors with varying sensing modalities to improve detection performance. The piezoelectric tactile sensor, incorporating a concentric ring microstructure, demonstrates a sensitivity coefficient of <inline-formula> <tex-math>$1.39~text {mV}cdot text { kPa}^{-{1}}$ </tex-math></inline-formula>. Conversely, the resistive strain sensor, characterized by a high-density reticular hollow structure, exhibits the highest gauge factor of 24.87. Furthermore, each sensor modality demonstrates excellent temporal response and stability, confirming its applicability in motion monitoring and Morse code transmission.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"12616-12626"},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839881","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}
Pub Date : 2025-03-13DOI: 10.1109/JSEN.2025.3548912
Henry E. Ventura-Grandez;Jonathan Quevedo;Itamar Salazar-Reque;Maria Armas-Alvarado;Luz Adanaque-Infante;Ruth Rubio-Noriega
Water pH measurement is vital as it provides fundamental information about its quality and suitability for agriculture, aquatic ecosystems, industry, and human consumption. Each of these applications may require numerical readings of acidity or alkalinity, preferably using tools that are already ubiquitous, such as cellphones. This work presents a microfluidic lab-on-a-chip system to measure the pH of liquid samples. We used purple cabbage as the colorimetric reagent to produce a 2640-image dataset with pH levels in the range of [2–12] on a polydimethylsiloxane (PDMS) microfluidic recipient. We fed our dataset to our parameterized deep neural network (DNN) to classify our samples and found an accuracy of 99.7%. In addition, we developed a mobile application with an easy-to-use graphic user interface that recognizes the microfluidic device shape, classifies the image’s color, and returns the pH level.
{"title":"Deep Neural Network-Assisted Microfluidic pH Sensor","authors":"Henry E. Ventura-Grandez;Jonathan Quevedo;Itamar Salazar-Reque;Maria Armas-Alvarado;Luz Adanaque-Infante;Ruth Rubio-Noriega","doi":"10.1109/JSEN.2025.3548912","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3548912","url":null,"abstract":"Water pH measurement is vital as it provides fundamental information about its quality and suitability for agriculture, aquatic ecosystems, industry, and human consumption. Each of these applications may require numerical readings of acidity or alkalinity, preferably using tools that are already ubiquitous, such as cellphones. This work presents a microfluidic lab-on-a-chip system to measure the pH of liquid samples. We used purple cabbage as the colorimetric reagent to produce a 2640-image dataset with pH levels in the range of [2–12] on a polydimethylsiloxane (PDMS) microfluidic recipient. We fed our dataset to our parameterized deep neural network (DNN) to classify our samples and found an accuracy of 99.7%. In addition, we developed a mobile application with an easy-to-use graphic user interface that recognizes the microfluidic device shape, classifies the image’s color, and returns the pH level.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"12609-12615"},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839879","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}
Pub Date : 2025-03-13DOI: 10.1109/JSEN.2025.3549027
Yu Wang;Wenzhe Zhang;Shengwu Zhao;Zhihong Deng
Gravity disturbance compensation technology is an important means to further enhance the positioning accuracy of high-precision inertial navigation systems (INSs). In response to the challenges faced by traditional gravity disturbance acquisition methods, which are computationally complex and time-consuming, this article proposes a gravity disturbance calculation and compensation method based on carrier motion constraints. First, using velocity information as a constraint, a conversion model is constructed for the low-frequency signal of gravity disturbance to calculate the low-order spherical harmonic model. This model significantly reduces the time cost required for the gravity disturbance model computation. Second, addressing the misalignment between the actual navigation coordinate system and the ideal navigation coordinate system caused by gravity disturbances, a coordinate system correction algorithm based on the direction cosine matrix of disturbances is proposed. This algorithm enhances the positioning accuracy and reliability of high-precision INSs. Experimental results show that the proposed low-order gravity disturbance compensation algorithm based on carrier motion constraints improves the positioning accuracy by 27.89% compared to traditional algorithms while reducing computation time by 64.84%. This meets the real-time positioning requirements for long-distance navigation conditions, especially suited for UUVs, AUVs, and submarine platforms with limited computational resources, as it optimizes processing efficiency while maintaining high accuracy.
{"title":"A Low-Order Gravity Disturbance Compensation Algorithm Based on Carrier Motion Constraints","authors":"Yu Wang;Wenzhe Zhang;Shengwu Zhao;Zhihong Deng","doi":"10.1109/JSEN.2025.3549027","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3549027","url":null,"abstract":"Gravity disturbance compensation technology is an important means to further enhance the positioning accuracy of high-precision inertial navigation systems (INSs). In response to the challenges faced by traditional gravity disturbance acquisition methods, which are computationally complex and time-consuming, this article proposes a gravity disturbance calculation and compensation method based on carrier motion constraints. First, using velocity information as a constraint, a conversion model is constructed for the low-frequency signal of gravity disturbance to calculate the low-order spherical harmonic model. This model significantly reduces the time cost required for the gravity disturbance model computation. Second, addressing the misalignment between the actual navigation coordinate system and the ideal navigation coordinate system caused by gravity disturbances, a coordinate system correction algorithm based on the direction cosine matrix of disturbances is proposed. This algorithm enhances the positioning accuracy and reliability of high-precision INSs. Experimental results show that the proposed low-order gravity disturbance compensation algorithm based on carrier motion constraints improves the positioning accuracy by 27.89% compared to traditional algorithms while reducing computation time by 64.84%. This meets the real-time positioning requirements for long-distance navigation conditions, especially suited for UUVs, AUVs, and submarine platforms with limited computational resources, as it optimizes processing efficiency while maintaining high accuracy.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13742-13752"},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839948","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}
Pub Date : 2025-03-13DOI: 10.1109/JSEN.2025.3549141
Yunfei Guo;Hao Zhang;Boting Lin;Hua Su;Yun Chen
To perform multiview (MV) multiextended target tracking (METT) with occlusion, a Gaussian belief propagation (GaBP)-based MV fusion (GaBP-MVF) algorithm is proposed. A concept of “virtual target” is presented to describe the state of an unobstructed part of the target. The “virtual targets” generate the “partial measurements” affected by occlusions through a spatial measurement model. Subsequently, the closed-form joint posterior probability density function (pdf) of virtual targets is formulated. After factorizing the pdf, a factor graph-based GaBP algorithm is derived for moment estimation of virtual targets’ states. Lastly, sensor-derived estimates are regarded as local estimates and forwarded to a fusion center for updating the global estimate. The virtual measurements are generated by a virtual measurement model (VMM) using the predicted global estimate. Then, the global estimate is updated by minimizing the distance between features extracted from virtual measurements and local estimates. The effectiveness of the proposed algorithm is evaluated in simulation and experiment.
{"title":"Gaussian Belief Propagation-Based Multiview Multiextended Target Tracking With Occlusion","authors":"Yunfei Guo;Hao Zhang;Boting Lin;Hua Su;Yun Chen","doi":"10.1109/JSEN.2025.3549141","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3549141","url":null,"abstract":"To perform multiview (MV) multiextended target tracking (METT) with occlusion, a Gaussian belief propagation (GaBP)-based MV fusion (GaBP-MVF) algorithm is proposed. A concept of “virtual target” is presented to describe the state of an unobstructed part of the target. The “virtual targets” generate the “partial measurements” affected by occlusions through a spatial measurement model. Subsequently, the closed-form joint posterior probability density function (pdf) of virtual targets is formulated. After factorizing the pdf, a factor graph-based GaBP algorithm is derived for moment estimation of virtual targets’ states. Lastly, sensor-derived estimates are regarded as local estimates and forwarded to a fusion center for updating the global estimate. The virtual measurements are generated by a virtual measurement model (VMM) using the predicted global estimate. Then, the global estimate is updated by minimizing the distance between features extracted from virtual measurements and local estimates. The effectiveness of the proposed algorithm is evaluated in simulation and experiment.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"14036-14048"},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840099","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}
The detection of carbon monoxide (CO) is of paramount importance for environmental monitoring, industrial safety, and public health. This study presents an all-fiber gas concentration monitoring technique based on tunable diode laser absorption spectroscopy (TDLAS), offering low gas consumption, high time resolution, high stability, and high precision. A 1-m-long negative curvature anti-resonant hollow core fiber (HCF) with a core diameter of $110~mu $ m is used for both gas containment and optical transmission. Experimental and theoretical simulations confirm that the response time of the system reaches 1.27 s at an overpressure of 98 kPa. Furthermore, the system achieves a relative standard deviation (RSD) of less than 2.5% and a minimum detection limit (MDL) of 0.220 ppm under optimal overpressure conditions. In addition, a spatial-resolved scanning imaging is demonstrated for the CO concentration distribution of 190-$mu $ m leakage point, enabling clear identification of the topographical features. This technology has potential in the fields of environmental monitoring, industrial safety, and public health.
{"title":"Highly Time-Resolved All-Fiber Sensor for Real-Time Carbon Monoxide Detection and Microleakage Diagnosis","authors":"Kaiyu Chai;Yipeng Zheng;Bo Hu;Zihao Zhou;Kaili Ren;Dongdong Han;Lipeng Zhu;Yongkai Wang;Lei Liang","doi":"10.1109/JSEN.2025.3546697","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3546697","url":null,"abstract":"The detection of carbon monoxide (CO) is of paramount importance for environmental monitoring, industrial safety, and public health. This study presents an all-fiber gas concentration monitoring technique based on tunable diode laser absorption spectroscopy (TDLAS), offering low gas consumption, high time resolution, high stability, and high precision. A 1-m-long negative curvature anti-resonant hollow core fiber (HCF) with a core diameter of <inline-formula> <tex-math>$110~mu $ </tex-math></inline-formula>m is used for both gas containment and optical transmission. Experimental and theoretical simulations confirm that the response time of the system reaches 1.27 s at an overpressure of 98 kPa. Furthermore, the system achieves a relative standard deviation (RSD) of less than 2.5% and a minimum detection limit (MDL) of 0.220 ppm under optimal overpressure conditions. In addition, a spatial-resolved scanning imaging is demonstrated for the CO concentration distribution of 190-<inline-formula> <tex-math>$mu $ </tex-math></inline-formula>m leakage point, enabling clear identification of the topographical features. This technology has potential in the fields of environmental monitoring, industrial safety, and public health.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13005-13011"},"PeriodicalIF":4.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839986","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}
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