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Coarse-to-Fine Sparse 3-D Reconstruction in THz Light Field Imaging 太赫兹光场成像中从粗到细的稀疏三维重建
IF 2.2
IEEE Sensors Letters Pub Date : 2024-09-04 DOI: 10.1109/LSENS.2024.3454567
Abdulraouf Kutaish;Miguel Heredia Conde;Ullrich Pfeiffer
{"title":"Coarse-to-Fine Sparse 3-D Reconstruction in THz Light Field Imaging","authors":"Abdulraouf Kutaish;Miguel Heredia Conde;Ullrich Pfeiffer","doi":"10.1109/LSENS.2024.3454567","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3454567","url":null,"abstract":"Terahertz (THz) light field imaging inherently allows capturing the 3-D geometry of a target but at the cost of an increased data volume. Compressive sensing techniques are instrumental in minimizing data acquisition requirements. However, they often rely on computationally expensive sparse reconstruction approaches with high memory footprint. This research introduces an advanced coarse-to-fine (CTF) sparse 3-D reconstruction strategy aimed at enhancing the precision of reconstructed images while significantly reducing computational load and memory footprint. By employing a sequence of sensing matrices of increasing resolution, our approach avoids falling into an ill-conditioned inversion and strikes a balance between reconstruction quality and computational efficiency. We demonstrate the effectiveness of this CTF strategy through its integration with several established algorithms, including basis pursuit (BP), fast iterative shrinkage-threshold algorithm (FISTA), and others. The results showcase the potential of the CTF approach to improve 3-D image reconstruction accuracy and processing speed in THz light field imaging.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142313082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Miniature pH Sensor in a Subcutaneous Injection Needle for Biofluid Sensing 用于生物流体传感的皮下注射针头微型 pH 传感器
IF 2.2
IEEE Sensors Letters Pub Date : 2024-09-04 DOI: 10.1109/LSENS.2024.3454486
Khengdauliu Chawang;Sen Bing;Jon Stellar;J.-C. Chiao
{"title":"A Miniature pH Sensor in a Subcutaneous Injection Needle for Biofluid Sensing","authors":"Khengdauliu Chawang;Sen Bing;Jon Stellar;J.-C. Chiao","doi":"10.1109/LSENS.2024.3454486","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3454486","url":null,"abstract":"The pH value in bodily fluids is a crucial diagnostic marker. Conventional glass-rod pH sensors display reliability in aqueous solutions, but the pH-sensitive glass membrane makes them prone to inaccuracies in viscous solutions due to elevated junction potentials and bulky design hinders miniaturization. To overcome this issue, this work introduces a new pH sensor design and fabrication that enables miniaturization and reliability in aqueous and viscous solutions and facilitates insertion into a needle for in vivo monitoring. Utilizing a printing technique for the application of iridium oxide (IrOx) and silver/silver chloride coating on a single flexible polyimide substrate offers cost-effectiveness and production scalability. The sensor then is tailored with a sharp blade to a narrow strip that fits into a 20-gauge needle. The electrochemical measurements demonstrate that electrodes produced through this method demonstrate an accuracy of up to 0.1 pH within a narrow pH range (7.35–7.45) in buffer solutions and real human serum tests.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10664516","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Efficient Cooperative Spectrum Sensing in UAV-Assisted Cognitive Wireless Sensor Networks 无人机辅助认知无线传感器网络中的高效合作频谱感知
IF 2.2
IEEE Sensors Letters Pub Date : 2024-09-04 DOI: 10.1109/LSENS.2024.3454718
Haoyu Liang;Jun Wu;Tianle Liu;Hao Wang;Weiwei Cao
{"title":"Efficient Cooperative Spectrum Sensing in UAV-Assisted Cognitive Wireless Sensor Networks","authors":"Haoyu Liang;Jun Wu;Tianle Liu;Hao Wang;Weiwei Cao","doi":"10.1109/LSENS.2024.3454718","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3454718","url":null,"abstract":"In order to meet the frequency requirements of unmanned aerial vehicles (UAVs), sensors assist UAVs in cooperative spectrum sensing (CSS) to identify available spectrum resources and opportunistically access the channel being underutilized by the primary user (PU). However, in such a UAV-assisted cognitive wireless sensor network (CWSN), the cooperative mode among multiple UAVs with built-in sensors may incur high overhead costs, resulting in the spectrum sensing performance degradation. Therefore, we introduce a differential sequential 1, which incorporates a differential mechanism and leverages the sequential idea based on the classical voting rule to enhance the CSS performance and efficiency. In view of this, we formulate three scenarios to characterize the PU activity and introduce a multislot cooperative mode within a single UAV with built-in sensor to realize cooperative gain. Finally, simulation results demonstrate that the superiority of our proposal with respect to the detection performance and sample size is evident.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reputation-Based Self-Differential Sequential Mechanism for Collaborative Spectrum Sensing Against Byzantine Attack in Cognitive Wireless Sensor Networks 认知式无线传感器网络中基于声誉的自差分序列机制--用于协作式频谱传感以对抗拜占庭攻击
IF 2.2
IEEE Sensors Letters Pub Date : 2024-09-04 DOI: 10.1109/LSENS.2024.3454708
Shengfei Xiao;Jun Wu;Peiyang Lin;Lei Qiao;Zhaoyang Qiu;Mingkun Su
{"title":"Reputation-Based Self-Differential Sequential Mechanism for Collaborative Spectrum Sensing Against Byzantine Attack in Cognitive Wireless Sensor Networks","authors":"Shengfei Xiao;Jun Wu;Peiyang Lin;Lei Qiao;Zhaoyang Qiu;Mingkun Su","doi":"10.1109/LSENS.2024.3454708","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3454708","url":null,"abstract":"In order to meet the increasing frequency demand for sensors and their related applications, cognitive radio (CR) technology has been integrated into wireless sensor networks, detecting available spectrum resources through collaborative spectrum sensing (CSS) among multiple sensors and avoiding harmful interference to the primary user. However, some malicious sensor nodes (MSNs) may also take advantage of collaborative opportunities to launch Byzantine attack, reducing the performance and efficiency of CSS. In order to suppress the negative impact of MSNs, this letter proposes a reputation-based self-differential sequential mechanism (R-SDSM) to defend against Byzantine attack. First, sensor nodes with high reputation value are prioritized to participate in CSS and complete the data fusion with more appropriate weight allocation. Furthermore, a self-differential sequential mechanism is proposed to reduce the reporting decisions required for the fusion center. Finally, numerical simulation results demonstrate that in contrast to other data fusion rules, the proposed R-SDSM provides higher detection accuracy and fewer reporting decisions.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An In-Pixel Ambient Suppression Method for Direct Time of Flight 直接飞行时间的像素内环境抑制方法
IF 2.2
IEEE Sensors Letters Pub Date : 2024-09-02 DOI: 10.1109/LSENS.2024.3453038
Ayman Morsy;Cédric Baijot;Gobinath Jegannathan;Thomas Lapauw;Thomas Van den Dries;Maarten Kuijk
{"title":"An In-Pixel Ambient Suppression Method for Direct Time of Flight","authors":"Ayman Morsy;Cédric Baijot;Gobinath Jegannathan;Thomas Lapauw;Thomas Van den Dries;Maarten Kuijk","doi":"10.1109/LSENS.2024.3453038","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3453038","url":null,"abstract":"This letter proposes a novel single photon avalanche diode (SPAD)-based pixel, designed for direct Time-of-Flight (ToF) imaging with in-pixel averaging, which provides a promising advancement in low-power and potentially high image resolution for outdoor applications. By utilizing a laser pulse and two orthogonal sinusoidal signals, the pixel averages out the detected ambient light while accumulating the laser pulse round-trip time. A prototype pixel array was fabricated using a 180 nm CMOS process, featuring a commercial SPAD cell. By characterizing one pixel and employing a 100 klux solar emulator as an ambient light source with a fixed 40 ambient-to-signal ratio over a 360\u0000<inline-formula><tex-math>$^{circ }$</tex-math></inline-formula>\u0000 phase shift, equivalent to 6 m detection range, the maximum detected accuracy error was 3.3%, with a 5 cm precision.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
NIR-EKF: Normalized Innovation Ratio-Based EKF for Robust State Estimation NIR-EKF：基于归一化创新比的稳健状态估计 EKF
IF 2.2
IEEE Sensors Letters Pub Date : 2024-08-30 DOI: 10.1109/LSENS.2024.3452205
Talha Nadeem;Khurrram Ali;Muhammad Tahir
{"title":"NIR-EKF: Normalized Innovation Ratio-Based EKF for Robust State Estimation","authors":"Talha Nadeem;Khurrram Ali;Muhammad Tahir","doi":"10.1109/LSENS.2024.3452205","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3452205","url":null,"abstract":"Sensors deployed in real-world conditions often produce measurements corrupted by outliers due to model uncertainties, changes in the surrounding environment, and/or data loss. As a result, managing these outliers becomes crucial for state estimation to avoid inaccurate estimations and a reduction in the reliability of results. To address this issue, we introduce a novel form of extended Kalman filter (EKF) based on the maximum a posteriori (MAP) principle for scenarios where outliers simultaneously occur in multiple dimensions. For detecting outliers during the filtering process, we introduce a novel variant of the normalized innovation ratio (NIR) test and embed it within the EKF framework. Our approach enhances the estimation accuracy and computational efficiency of state estimation process even when data from several sensors simultaneously contain outliers.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fault Diagnosis Algorithm for Dry-Type Transformer Based on Deep Learning of Small-Sample Acoustic Array Signals 基于小样本声学阵列信号深度学习的干式变压器故障诊断算法
IF 2.2
IEEE Sensors Letters Pub Date : 2024-08-29 DOI: 10.1109/LSENS.2024.3451470
Qinglu Zheng;Youyuan Wang;Zhanxi Zhang
{"title":"Fault Diagnosis Algorithm for Dry-Type Transformer Based on Deep Learning of Small-Sample Acoustic Array Signals","authors":"Qinglu Zheng;Youyuan Wang;Zhanxi Zhang","doi":"10.1109/LSENS.2024.3451470","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3451470","url":null,"abstract":"The normal operation of electrical equipment is related to the stability of the power system. The dry-type transformer, as an important part of the distribution network, directly guarantees that users can use high-quality electricity. At present, most of the fault diagnosis of dry-type transformers is limited to the detection and maintenance of power outages, and there are few studies on nondestructive testing of power outages. In this letter, the operation state of the dry-type transformer is judged by the small-sample acoustic array signal, and the highly correlated intrinsic mode components are extracted by empirical mode decomposition (EMD); the highly correlated intrinsic mode components are further denoised by combining the adaptive wavelet basis transform. Then, the Hilbert transform is used to fuse the multichannel signals to form the original eigentensor. The principal component analysis is used to reduce the dimensionality of the original eigentensor to reduce the feature information surplus. The improved residual network is used to classify different features of dry-type transformers. It is verified that the proposed method has a high accuracy of 97.8% under the premise of small-sample datasets, which is better than that of the same type of detection method and has good robustness.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Estimation of Tension Force in Tension Members Using GRU Algorithm Based on Yoke-Type Elasto-Magnetic Sensor Data 基于磁轭型弹性磁传感器数据的 GRU 算法估算受拉构件的拉力
IF 2.2
IEEE Sensors Letters Pub Date : 2024-08-29 DOI: 10.1109/LSENS.2024.3451405
Ho-Jun Lee;Sae-Byeok Kyung;Sung-Won Kim;Eun-Yul Lee;Ju-Won Kim
{"title":"Estimation of Tension Force in Tension Members Using GRU Algorithm Based on Yoke-Type Elasto-Magnetic Sensor Data","authors":"Ho-Jun Lee;Sae-Byeok Kyung;Sung-Won Kim;Eun-Yul Lee;Ju-Won Kim","doi":"10.1109/LSENS.2024.3451405","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3451405","url":null,"abstract":"This letter proposes a method to the estimation of tension force in tension members using the grated recurrent unit (GRU) algorithm. In this letter, a yoke-type elasto-magnetic (E/M) sensor was developed based on numerical ANSYS Maxwell simulations to enhance the applicability through the structural improvement of the existing solenoid-type magnetized E/M sensor. The induced voltage signal collected based on the yoke-type E/M sensor was applied to the GRU algorithm. As a result of applying the GRU model to the induced voltage signal data according to the change in tension force of the yoke-type E/M sensor, it was proven that high-accuracy tension force estimation is possible. These results suggest new possibilities for structural health monitoring technology through nondestructive testing. This study presents the applicability of artificial-intelligence-based techniques in nondestructive measurements of tension members for the health monitoring of structures.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Unitary Root-MUSIC Method With Nystrom Approximation for 3-D Sparse Array DOA Estimation in Sensor Networks 用于传感器网络中三维稀疏阵列 DOA 估计的带有 Nystrom 近似值的单元根-MUSIC 方法
IF 2.2
IEEE Sensors Letters Pub Date : 2024-08-29 DOI: 10.1109/LSENS.2024.3451723
Veerendra D;Miguel Villagomez-Galindo;Ana Beatriz Martínez Valencia;Niranjan KR;Arora Jasmineet Kaur;Upendra Kumar Potnuru;Jasgurpreet Singh Chohan;Bade Venkata Suresh;Sudhanshu Maurya
{"title":"Unitary Root-MUSIC Method With Nystrom Approximation for 3-D Sparse Array DOA Estimation in Sensor Networks","authors":"Veerendra D;Miguel Villagomez-Galindo;Ana Beatriz Martínez Valencia;Niranjan KR;Arora Jasmineet Kaur;Upendra Kumar Potnuru;Jasgurpreet Singh Chohan;Bade Venkata Suresh;Sudhanshu Maurya","doi":"10.1109/LSENS.2024.3451723","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3451723","url":null,"abstract":"This letter addresses the challenge of efficient direction of arrival (DOA) estimation in 3-D sparse arrays, crucial for applications, such as radar and wireless communication systems. We introduce a novel methodology that combines the Nystrom approximation with the unitary root-multiple signal classification (MUSIC) algorithm to precisely estimate DOAs while significantly reducing computational complexity. Our approach strategically selects a subset of sensors using the Nystrom approximation, resulting in a notable decrease in simulation time compared to conventional methods, such as Root-MUSIC and MR-ESPRIT. Extensive simulations validate the efficacy of our method, demonstrating a reduction of up to 39% in simulation time with a sensor subset size of 20. This technique, which enhances efficiency, has the potential to transform DOA estimation in 3-D sparse arrays, making it suitable for real-world applications that demand rapid and accurate signal processing.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Multimodel Stacking and Ensemble Framework for Human Activity Recognition 人类活动识别的多模型堆叠和集合框架
IF 2.2
IEEE Sensors Letters Pub Date : 2024-08-29 DOI: 10.1109/LSENS.2024.3451960
Abisek Dahal;Soumen Moulik
{"title":"The Multimodel Stacking and Ensemble Framework for Human Activity Recognition","authors":"Abisek Dahal;Soumen Moulik","doi":"10.1109/LSENS.2024.3451960","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3451960","url":null,"abstract":"Human activity recognition (HAR) plays an important role in various domains, such as healthcare, elderly care, sports, gait analysis, and security surveillance. Despite its significance in various fields, attaining a high accuracy remains a formidable challenge. This letter proposes a multimodel stacking and ensemble framework for HAR. The proposed model uses a horizontal stacking approach integrating three different model, namely, ridge regression, LightGBM, and gradient boosting machine (GBM) combined to form a blended model. GBM is also serves as the meta-learner in this configuration. By leveraging this stacking framework, our model significantly enhances the accuracy of HAR. The proposed model achieves remarkable performance in publicly available datasets with accuracy rates of 98% on the HCI-HAR dataset, 99.10% on the WISDM dataset, and 99.20% on the mHealth dataset thereby surpassing existing benchmarks in machine learning. Therefore, the proposed model uses an ensemble stacking model to represent a promising avenue for enhancing HAR and has potential applications in various fields.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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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