IEEE Sensors Journal最新文献

{"title":"Bistatic InISAR Baseline Optimization for Joint Antenna Attitude and Observation Area Estimation in Stripmap SAR","authors":"Wenshuo Qian;Junling Wang;Lizhi Zhao;Haiguang Li;Fujie Tang","doi":"10.1109/JSEN.2026.3716653","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3716653","url":null,"abstract":"Accurate geolocation of ground areas observed by spaceborne synthetic aperture radar (SAR) operating in stripmap mode is critical for active defense applications. This article proposes a joint estimation framework for antenna attitude and ground observation area in spaceborne stripmap SAR, utilizing baseline-optimized ground-based bistatic interferometric ISAR (InISAR). First, the time-varying geolocation problem of ground observation areas is reformulated as a fixed antenna attitude estimation task using a stripmap SAR observation geometry model. Following this, a robust adaptive weighted normal estimation (AWNE) algorithm is developed to suppress outlier interference by adaptively weighting scatterers located at the parabolic antenna’s outer edge. Recognizing that height estimation accuracy fundamentally constrains both attitude estimation and ground-area geolocation precision, we further propose baseline-optimization deployment strategies for mobile receivers within the bistatic InISAR system to maximize height estimation accuracy. An InISAR baseline geometric model is established to quantify height estimation performance across baseline configurations, deriving optimal interferometric baseline vectors. The northward deviation angle parameter is then introduced to characterize mobile receiver positioning, enabling efficient deployment in practical scenarios. Experimental results demonstrate the effectiveness and robustness of the proposed algorithms in enhancing the accuracy of both antenna attitude estimation and observed area geolocation.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"26534-26550"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11631722","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871268","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}

{"title":"OG-RMGIB: A Novel 2-D Off-Grid Regularized Matrix Generalized Inverse Beamforming for Acoustic Source Identification","authors":"Shuaiyong Li;Sihan Lin;Pei Shen;Youwei Yu","doi":"10.1109/JSEN.2026.3714368","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3714368","url":null,"abstract":"Traditional grid-based beamforming methods often suffer from performance degradation caused by basis mismatch when dealing with practical sound source localization problems, and this becomes particularly pronounced at low frequencies. To address this challenge, this article proposes a novel 2-D off-grid regularized-matrix generalized inverse beamforming (OG-RMGIB) method to achieve high-accuracy acoustic source identification. Within the framework of generalized inverse beamforming (GIB), the proposed method establishes a new off-grid modeling scheme that preserves the inherent high spatial resolution of GIB. More importantly, a 3-D regularization matrix is innovatively incorporated to enhance stability and robustness. The algorithm begins by performing a first-order Taylor expansion of the steering vector around the initial estimate, yielding a source strength formulation that explicitly embeds off-grid deviation information. Subsequently, an alternating iterative strategy is employed to jointly estimate the source locations and strengths. Experimental results demonstrate that the proposed approach effectively mitigates basis mismatch and maintains high localization accuracy even under low-frequency conditions. The method significantly improves both localization precision and spatial discrimination capability, highlighting its strong potential for practical applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"26319-26337"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871298","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}

{"title":"CIFA: A Causal-Informed Feature Alignment Framework for Cross-Domain Acoustic Fault Diagnosis","authors":"Zhaoquan Ye;Shengwei Li;Lin Zhang;Fanghong Guo;Dan Zhang","doi":"10.1109/JSEN.2026.3714141","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3714141","url":null,"abstract":"In industrial applications such as uncrewed aerial vehicle (UAV)-based inspections, acoustic sensors have emerged as a pivotal data source for equipment fault diagnosis, owing to their advantages of noncontact sensing, cost-effective deployment, and rich spectral information content. However, during the actual sensing process, acoustic signals often exhibit significant distribution shifts induced by fluctuations in operating conditions, variations in equipment models, and changes in the acoustic properties of the acquisition environment. These shifts severely impair the cross-domain generalization capability of diagnostic models. To address this challenge, a causal-informed feature alignment (CIFA) framework is proposed for cross-domain acoustic fault diagnosis in this article. Specifically, an X-learner causal effect estimator is introduced to estimate the feature level effects of source domain features on fault labels, thereby identifying causally relevant and transferable features. In addition, target domain features are identified through confidence-driven pseudo labeling and alignment with the source domain by using an adaptive feature alignment (AFA) approach, thus minimizing the discrepancy between the two domains. The experimental results obtained from a publicly available UAV dataset indicate that the proposed method is highly accurate for all three cases, with an average accuracy of 71.15%.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"26307-26318"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871387","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}

{"title":"Composite Disturbance Filter-Based Integrity Monitoring Under Unknown Disturbance Inputs","authors":"Jianchun Zhang;Dong Zhao;Chenlong Li;Xiang Yu;Lei Guo","doi":"10.1109/JSEN.2026.3715877","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3715877","url":null,"abstract":"The Kalman filter (KF)-based integrity monitoring against sensor faults fails to consider the impact of unknown disturbance inputs on fault detection (FD) and protection level (PL) calculation. To alleviate this impact, this article proposes an integrity monitoring method based on the composite disturbance filter (CDF) under unknown disturbance inputs. First, the CDF fusion framework is presented. On this basis, the error propagation analysis is conducted to establish the state estimation error recursion equation. Furthermore, an innovation-based FD algorithm is proposed within the CDF framework, and the corresponding minimum detectable bias (MDBs) is derived. Finally, the PL of the navigation system is constructed based on the error recursion equation and the MDB. Simulation results demonstrate that the proposed integrity monitoring algorithm can reduce the false alarm rate (FAR) of faults under disturbance inputs, and the calculated PL effectively tracks and envelops the position error variation, thereby achieving the reliable protection of the navigation solution.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"26500-26511"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871421","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}

{"title":"Synergistic Blood Pressure Estimation via Contactless mmWave Radar and Imaging Photoplethysmography: A Feasibility Study","authors":"Boyuan Gu;Haiyang Sun;Yongjie Liu;Guangji Ma;Guanghao Sun;Xiaorong Ding","doi":"10.1109/JSEN.2026.3706110","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3706110","url":null,"abstract":"Continuous, noncontact blood pressure (NCBP) monitoring holds significant promise for pervasive cardiovascular care, yet single-modality approaches—such as imaging photoplethysmography (iPPG)—remain constrained by environmental artifacts, skin-tone sensitivity, and the absence of proximal cardiac mechanical information. This study investigates the feasibility of a dual-modality sensing paradigm that synergistically integrates facial iPPG with posterior-facing, frequency-modulated continuous wave (FMCW) millimeter-wave radar to capture complementary hemodynamic cues: distal optical volumetric fluctuations and proximal cardiac micromotion radar motion signals (RMSs). To bridge the morphological disparity between these heterogeneous streams, we develop an end-to-end deep-learning architecture, bidirectional long short-term memory (BiLSTM)-MS-dilated convolutional neural network (DiCNN), which leverages multiscale dilated convolutions for spatial feature extraction and bidirectional long short-term memory for temporal dependency modeling. In a controlled feasibility study involving 15 healthy participants across distinct hemodynamic states (resting, deep breathing (DB), and postexercise), the proposed framework achieved a mean absolute difference (MAD) of 4.71 mmHg for systolic blood pressure (SBP) and 4.60 mmHg for diastolic blood pressure (DBP) under resting conditions, with consistent performance during physiological perturbations (SBP: 6.35 mmHg, DBP: 4.95 mmHg for DB; SBP: 5.33 mmHg, DBP: 4.96 mmHg for postexercise). Statistically significant improvements over unimodal baselines validate the complementary nature of the dual-modality inputs, while ablation studies confirm the architectural contributions of each module. Even without calibration (0%), the model achieves an SBP/DBP MAD of 7.52/6.85 mmHg, indicating that the framework retains a measurable noncalibrated baseline capability, while brief calibration further improves subject-level personalization. These preliminary findings demonstrate the viability of mmWave-iPPG fusion as a promising pathway toward robust, unobtrusive NCBP monitoring, warranting further investigation in larger and more diverse cohorts.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"26607-26617"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871439","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}

{"title":"ISAR Motion Parameter Estimation Based on Polynomial Phase Coefficient Plane Constraint","authors":"Lang Yang;Jing Yang;Xuelian Luo;Li Wang;Yong Luo","doi":"10.1109/JSEN.2026.3712012","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3712012","url":null,"abstract":"This article investigates motion parameter estimation for inverse synthetic aperture radar (ISAR) imaging of maneuvering targets. A fundamental theoretical discovery is presented: for targets undergoing complex motion involving angular acceleration and higher order terms, when the rotational phase history is expanded into a polynomial series, the coefficient of each order term satisfies a linear relationship with respect to Doppler frequency and range coordinate, implying that these polynomial phase coefficients lie on planes in parameter space. This geometric constraint provides redundant information for robust motion estimation. Exploiting this finding, a parameter estimation method is developed for targets exhibiting angular acceleration. The method first extracts the chirp rate, Doppler frequency, and range position of multiple scatterers by combining the CLEAN technique with a dechirp operation, then fits these measurements to a plane via the random sample consensus (RANSAC) algorithm to reject outliers caused by noise or multiscatterer interference. The effective rotational velocity (ERV) and acceleration are then analytically decoupled from the plane coefficients. Finally, the polar format algorithm (PFA) is applied for motion compensation and focused imaging. The proposed method overcomes the limitation of existing approaches that rely on only a few selected scatterers, and at the same time, avoids the high computational cost of global search-based optimization. Comprehensive simulation experiments and measured data validation are conducted to demonstrate the effectiveness of the proposed method.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"26164-26174"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871457","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}

{"title":"Resolver Envelope Calibration via Adaptive Notch and Phase Compensation","authors":"Lihong Yu;Huiyang Shao;Xinmin Li;Guohua Lian;Guanghang Qiao","doi":"10.1109/JSEN.2026.3717271","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3717271","url":null,"abstract":"Nonideal envelope signals—characterized by amplitude asymmetry, phase shift, and DC offset—degrade the decoding accuracy of the resolver-to-digital converter (RDC). To address this, an envelope signal calibration method via an adaptive notch filter (ANF) and a dual-channel phase shift compensation strategy is proposed, within a framework that combines offline parameter estimation with online calibration and decoding. In the offline stage, the conventional angular frequency estimator is replaced with a harmonic-resistant estimator based on ANF and system identification. In the online stage, a dual-channel phase shift compensation strategy is proposed. Unlike the conventional estimator that ignores harmonics, this scheme explicitly models envelope harmonic distortion, improving the harmonic immunity of the offline estimator. This yields a high-precision angular frequency reference for subsequent gradient estimation, enhancing the reliability of amplitude, phase shift, and DC offset estimation. Moreover, the proposed phase shift compensation strategy accounts for phase shifts in both channels and compensates for their induced errors with high precision. Simulation and experimental results confirm that under harmonic distortion conditions, the proposed scheme improves both angular frequency estimation and phase shift calibration, thereby enhancing overall RDC decoding accuracy.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"26019-26031"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871460","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}

{"title":"Prototypical Modal Rebalance-Based Heterogeneous Sensor Fusion for Nondestructive Pork Freshness Detection","authors":"Leben Niu;Wenyu Li;Yapeng Wang;Xu Yang;Sio-Kei Im;Miao Zhang","doi":"10.1109/JSEN.2026.3712779","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3712779","url":null,"abstract":"Pork, as the main source of animal protein, accounts for approximately 34% of global meat consumption and requires reliable freshness assessment to ensure safety and quality. Traditional methods, such as electrical impedance spectroscopy and microbial analysis, can effectively evaluate meat freshness but often suffer from destructiveness, complex equipment, or low efficiency. While nondestructive single-modality sensors (e.g., RGB cameras or gas sensors) have emerged as alternatives, they are inherently constrained by environmental susceptibility and incomplete feature representation. Integrating visual and olfactory signals provides a promising solution; however, fusing heterogeneous sensor data frequently triggers a “modal imbalance” problem, where the dominant modality suppresses the weaker one during deep learning optimization. To address this engineering challenge, this study develops an engineering-oriented heterogeneous sensor data fusion prototype, integrating the prototypical modal rebalance (PMR) strategy for nondestructive pork freshness detection. First, we adapt an extended adaptive multiscale attention U-Net (AMSAU-Net) as a visual preprocessing module. Acting as a hard attention mechanism, it precisely segments lean meat regions to filter background noise and extract high-purity visual features. Furthermore, the PMR strategy is introduced to dynamically balance the learning dynamics between the visual and olfactory modalities, maximizing their complementary benefits. Experimental results demonstrate that the proposed multimodal system achieves an outstanding accuracy of 99.58% across three freshness levels based on leave-one-subject-out cross-validation (LOSOCV) using storage-time proxy labels, while total volatile basic nitrogen (TVB-N) measurements are mainly utilized for external validation and biochemical calibration. Comprehensive ablation studies across multiple classifiers confirm that the PMR strategy significantly improves the recall rate by effectively compensating for the weaker olfactory signals, providing a highly accurate and reproducible prototypical solution for the freshness classification of cut pork samples under controlled conditions.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"26203-26217"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871467","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}

{"title":"High-Performance Quartz and Langasite (LGS) Piezoelectric Sensors: Multimode Mechanisms and Extreme Environment Deployment: A Review","authors":"Junmin Jing;Zengxing Zhang;Wenze Deng;Quanzhuo He;Weihong Ouyang;Ziming Ren;Libo Gao;Chenyang Xue","doi":"10.1109/JSEN.2026.3714873","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3714873","url":null,"abstract":"Quartz and langasite (LGS) stand as core piezoelectric materials for high-performance sensors, owing to their exceptional mechanical stability, prominent piezoelectric response, and superior adaptability to extreme operating conditions. With the growing demand for precise parameter monitoring in harsh scenarios, including deep oil/gas wells, deep-sea exploration, nuclear engineering, and aerospace systems-quartz/LGS sensors have been extensively investigated for their ability to withstand temperatures up to 1200 °C, pressures exceeding 100 MPa, and deliver high-precision measurement. This article provides a comprehensive and systematic review of the multimode operating mechanisms of quartz/LGS sensors, covering resonant modes (thickness shear mode (TSM), double-ended tuning fork (DETF) mode), surface acoustic wave (SAW) mode, bulk acoustic wave (BAW) mode, and dual-mode synergistic mechanisms. Key adaptation technologies for extreme environments are elaborated, including high-temperature material selection, high-pressure structural reinforcement, temperature/pressure compensation algorithms, and high-reliability packaging. Typical application scenarios and engineering deployment schemes are analyzed in detail for oil/gas exploration, deep-sea research, nuclear industry, and high-temperature manufacturing. Finally, current research bottlenecks are summarized, and future trends are proposed, including material innovation, mechanism breakthroughs, technology integration, and application expansion. This review offers a complete theoretical foundation and technical reference for the upgrading and industrialization of extreme-environment sensing technology.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"25358-25372"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871493","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}

{"title":"Design of Highly Uniform Cylindrical Coils Based on an Improved Sand Cat Swarm Optimization Algorithm for Small-Animal Magnetocardiography","authors":"Ziyuan Huang;Qinghai Ren;Hao Fang;Qiumin Wang;Rui Shang;Xue Xia","doi":"10.1109/JSEN.2026.3716953","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3716953","url":null,"abstract":"Small-animal magnetocardiography (MCG) imposes strict requirements on magnetic field systems because of the limited measurement space, weak cardiac magnetic signals, and the need for close-range sensor placement. To address these challenges, this article proposes a miniature cylindrical uniform-field coil design method for compact weak magnetic measurement systems. The proposed method reconstructs the coil current distribution using the target field method (TFM) and combines it with a Lévy-flight-enhanced sand cat swarm optimization (SCSO) algorithm to adaptively optimize the regularization parameter, thereby improving magnetic field uniformity while maintaining a compact coil structure. Under a <inline-formula> <tex-math>$60times 60times 60$ </tex-math></inline-formula> mm target region and a 1% field uniformity constraint, the cylindrical coil configuration reduces the required packaging volume by 33.2% compared with the biplanar coil, showing higher spatial efficiency. After SCSO-based optimization, the resulting SCSO-optimized cylindrical coil (SCSO coil) reduces the maximum normalized error from 0.889% to 0.331% in simulation. In the flexible printed circuit prototype experiment, the maximum normalized error of the SCSO coil is reduced from 0.919% to 0.220%. A further preliminary mouse MCG experiment indicates that the SCSO coil can provide a compact and uniform magnetic environment for miniature biomagnetic measurements. These results demonstrate the applicability of the SCSO coil to small-animal MCG and other compact weak magnetic measurement scenarios.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 17","pages":"25572-25581"},"PeriodicalIF":4.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871064","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}