IEEE Transactions on Instrumentation and Measurement最新文献_第2页

Suppression of Heading Error in Bell-Bloom Atomic Magnetometer by Controlling RF Magnetic Field 通过控制射频磁场抑制钟罩式原子磁力计的方向误差

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-28 DOI: 10.1109/TIM.2024.3485395

Jun Zhu;Liwei Jiang;Jiali Liu;Xin Zhao;Chi Fang;Qi Shao;Yuntian Zou;Zhuo Wang

{"title":"Suppression of Heading Error in Bell-Bloom Atomic Magnetometer by Controlling RF Magnetic Field","authors":"Jun Zhu;Liwei Jiang;Jiali Liu;Xin Zhao;Chi Fang;Qi Shao;Yuntian Zou;Zhuo Wang","doi":"10.1109/TIM.2024.3485395","DOIUrl":"https://doi.org/10.1109/TIM.2024.3485395","url":null,"abstract":"The atomic magnetometers operated in Earth-scale magnetic field are susceptible to the nonlinear Zeeman (NLZ) effect, resulting in multiple resonance peaks and heading error, which restricts their practical applications. We introduce a spin-locking method based on magnetic field modulation to overcome the NLZ effect and thus suppress the heading error in atomic magnetometers. The suppression effect of spin-locking is proportional to the amplitude of the modulation field. However, an excessively high modulation field amplitude can lead to broadening of the measurement linewidth. A novel model characterizing the linewidth for the amplitude of modulated magnetic field under different environmental magnetic field is established by considering the NLZ effect. From the test results, the novel model can more accurately predict the linewidth under different environmental magnetic fields compared with traditional models. The optimized amplitude of modulated magnetic field is obtained based on the linewidth model, and the heading error is suppressed by about 80% within the magnetic field inclination angle of 28.76°. The theory and method presented here are important for the application of magnetometers in Earth-scale magnetic field, which can suppress the heading error while keeping the linewidth unchanged.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MARFPNet: Multiattention and Adaptive Reparameterized Feature Pyramid Network for Small Target Detection on Water Surfaces MARFPNet：用于水面小目标检测的多注意力和自适应重参数化特征金字塔网络

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-28 DOI: 10.1109/TIM.2024.3485463

Quanbo Ge;Wenjing Da;Mengmeng Wang

{"title":"MARFPNet: Multiattention and Adaptive Reparameterized Feature Pyramid Network for Small Target Detection on Water Surfaces","authors":"Quanbo Ge;Wenjing Da;Mengmeng Wang","doi":"10.1109/TIM.2024.3485463","DOIUrl":"https://doi.org/10.1109/TIM.2024.3485463","url":null,"abstract":"The images captured by unmanned aerial vehicles (UAVs) are often limited in scale and feature information, making it challenging for current detection algorithms to learn the features of objects effectively. This limitation hampers accurate identification of small objects on water surfaces. We introduce a multiattention and adaptive reparameterized feature pyramid network for small target detection on water surfaces (MARFPNet) to tackle this issue. First, to address the loss of small object features during extraction, we improved the attention mechanism based on the characteristics of small objects and proposed a multiattention module, integrating it into the feature extraction process. Second, to address the semantic information of small objects being retained mostly in shallow feature maps and not fully utilized, we introduced an adaptive reparameterized generalized feature pyramid network (Adaptive_RepGFPN). This module reorganizes features, expands the fusion scale, and incorporates adaptive weighting in the concat operation. Third, to overcome the challenge of ineffective restoration of feature map information by upsampling, we introduce the Dysample. Finally, to address the problem of the loss function being sensitive to scale changes, we propose the normalized Wasserstein distance (NWD) loss function to reduce the sudden drop in loss due to scale changes. We conducted experiments on VisDrone, SeaDronsSee, and the self-build dataset. MARFPNet showed higher accuracy compared to other detection algorithms. Notably, on the self-build dataset, mAP50 and mAP50:95 improved by 9.1% and 3.5% over the baseline network. This demonstrates MARFPNet’s effectiveness and suitability for detecting small targets in drone aerial photography on water surfaces.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prototypical Contrastive Domain Adaptation Network for Nonstationary EEG Classification 用于非稳态脑电图分类的原型对比域自适应网络

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-28 DOI: 10.1109/TIM.2024.3476618

Donglin Li;Jiacan Xu;Yuxian Zhang;Dazhong Ma;Jianhui Wang

{"title":"Prototypical Contrastive Domain Adaptation Network for Nonstationary EEG Classification","authors":"Donglin Li;Jiacan Xu;Yuxian Zhang;Dazhong Ma;Jianhui Wang","doi":"10.1109/TIM.2024.3476618","DOIUrl":"https://doi.org/10.1109/TIM.2024.3476618","url":null,"abstract":"The identification of electroencephalography (EEG) signals’ cross sessions and subjects remains challenging due to the variability of data caused by extraneous factors and individual differences in EEG signals. Existing domain-adaptive transfer methods using cross-domain labeled samples for classification are too coarse and could lead to negative transfer problems. To solve this problem, we propose a prototypical contrastive domain adaptation (PCDA) network in this article. First, we align the data from different domains to reduce the data distribution differences for supporting the subsequent model construction. Then, a conditional domain adversarial network is used in the feature extraction stage to achieve domain alignment and learn deep feature representations. Second, we propose a scoring method to equivalently quantify the similarity of data from different domains using resting-state data and select similar source domain data to fine-tune the model. Finally, we propose a prototypical contrastive (PC) learning module. In-domain PC learning captures and compares the category-wise semantic structure of the data and the learned representations to enable the clustering of similar features. Cross-domain PC learning encodes and compares the semantic structure in shared embedding space to enable self-supervised feature alignment and reduce negative transfer. The experimental results show that the PCDA network achieves better results on the datasets of brain-computer interface (BCI) Competition IV II-a and II-b, and the ablation experiments validate the efficacy of the method.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142565593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying the Optical Fiber Based on the Compact OFDR System via Reflecting Estimation 通过反射估计识别基于紧凑型 OFDR 系统的光纤

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-25 DOI: 10.1109/TIM.2024.3413156

Zheyi Yao;Zhentao Song;Guohua Gu;Qian Chen;Shenghang Zhou;Xiubao Sui

引用次数: 0

A Novel Data-Driven-Based Anti-Disturbance Fault-Tolerant Control Method With Application to Franka-Panda Robot 基于数据驱动的新型抗干扰容错控制方法在弗兰卡-熊猫机器人上的应用

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-24 DOI: 10.1109/TIM.2024.3481544

Zi-Yuan Dong;Yu Xinyi;Yan Wei;Libo Zhou;Linlin Ou

{"title":"A Novel Data-Driven-Based Anti-Disturbance Fault-Tolerant Control Method With Application to Franka-Panda Robot","authors":"Zi-Yuan Dong;Yu Xinyi;Yan Wei;Libo Zhou;Linlin Ou","doi":"10.1109/TIM.2024.3481544","DOIUrl":"https://doi.org/10.1109/TIM.2024.3481544","url":null,"abstract":"Sensor faults have always been an essential and challenging problem in data-driven fault-tolerant control (DDFTC). Nevertheless, few studies in DDFTC have simultaneously considered the FTC problem under disturbance. To address the issue with both measurement noise and sensor fault, an iterative learning-based fault-tolerant control (ILFTC) strategy is presented when dynamics are completely unknown. First, an improved data-based unscented Kalman filter (UKF) mechanism is designed for the FTC scheme, which enhances the feasibility of the data-driven approaches under measurement disturbance. Then, the adaptive estimation algorithm with a switching mechanism is designed to improve the flexibility of the controller. Furthermore, a data-driven fault detection method is constructed under the framework of a broad learning system (BLS), which improves the detection accuracy while avoiding the need for precise model parameters in designing the fault detection observer. Finally, simulations and an application to the Franka-Panda robot demonstrate the superiority of the presented algorithm. Compared with the existing DDFTC schemes, smaller tracking errors and superior data signal-to-noise ratio (SNR) can be obtained.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142565602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced Azimuth Determination in Drilling via Piecewise Polynomial Fitting and Interpolation 通过片断多项式拟合和插值增强钻井中的方位角测定

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-23 DOI: 10.1109/TIM.2024.3485449

Tao Guo;Weibin Cheng;Yifei Zhang;Shaobing Hu

{"title":"Enhanced Azimuth Determination in Drilling via Piecewise Polynomial Fitting and Interpolation","authors":"Tao Guo;Weibin Cheng;Yifei Zhang;Shaobing Hu","doi":"10.1109/TIM.2024.3485449","DOIUrl":"https://doi.org/10.1109/TIM.2024.3485449","url":null,"abstract":"Precise geomagnetic azimuth measurement is essential for automation and intelligent operations in deep-Earth and deep-sea resource exploration. However, during drilling, the main sources of azimuth error include the inherent distortion of triaxial accelerometer and triaxial magnetometer, which requires prior calibration. To address this issue, we focus on static azimuth measurements by analyzing the error propagation relationship, developing a comprehensive error correction model, and proposing a correction method that combines piecewise polynomial fitting and improved interpolation. Finally, the proposed algorithm was experimentally validated using a high-precision inclinometer calibration platform. The experiment compared the error correction effects of the three-step combination method and the proposed method. At a confidence level of \u0000<inline-formula> <tex-math>$p = 0.95$ </tex-math></inline-formula>\u0000 and an axial tilt of \u0000<inline-formula> <tex-math>$I = 0.594$ </tex-math></inline-formula>\u0000, dA decreased from (\u0000<inline-formula> <tex-math>$3.1^{circ }~pm ~0.9^{circ }$ </tex-math></inline-formula>\u0000) to (\u0000<inline-formula> <tex-math>$1.8^{circ }~pm ~0.5^{circ }$ </tex-math></inline-formula>\u0000) and (\u0000<inline-formula> <tex-math>$7times 10^{mathbf {-4}}~pm ~3.7times 10^{mathbf {-2}}$ </tex-math></inline-formula>\u0000) for the traditional and proposed method, respectively. The proposed method demonstrates good performance in azimuth reconstruction and meets the practical engineering demands of azimuth calibration in measurement-while-drilling (MWD) system.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PRO-CLIP: A CLIP-Based Category Measurement Network Through Prototype and Regularized Optimal Transportation PRO-CLIP：通过原型和正则化优化运输实现基于 CLIP 的类别测量网络

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-23 DOI: 10.1109/TIM.2024.3485403

He Cao;Yunzhou Zhang;Shangdong Zhu;Lei Wang

{"title":"PRO-CLIP: A CLIP-Based Category Measurement Network Through Prototype and Regularized Optimal Transportation","authors":"He Cao;Yunzhou Zhang;Shangdong Zhu;Lei Wang","doi":"10.1109/TIM.2024.3485403","DOIUrl":"https://doi.org/10.1109/TIM.2024.3485403","url":null,"abstract":"In unstructured environments, robots are likely to encounter desktop objects that they have never seen before. Classifying these objects precisely is a prerequisite for accomplishing object-specific manipulation tasks. However, it is time-consuming to collect large-scale object classification datasets. Inspired by the prompt tuning methods, we propose the PRO-CLIP network, which is a category measurement method for desktop objects. Specifically, PRO-CLIP performs few-shot classification based on the knowledge from pretrained vision-language model (VLM). It utilizes token-level and prompt-level optimal transportations (OTs) to jointly fine-tune the learnable vision-language prompts. For token-level stage, we propose the image patch reweighting (PR) mechanism to make alignments focus on the image patches that are close to the patch prototypes. This allows the patch embeddings have converging category representations, which reduces intraclass differences of visual features. For prompt-level stage, we propose a cascading OT (COT) module to simultaneously consider task-irrelevant knowledge in zero-shot features and task-specific knowledge in few-shot features. Due to the generalization performance of task-irrelevant knowledge, the proposed module achieves feature regularization during OT. Finally, we propose the UP loss to supervise the whole network. It contains unbalanced logit-level consistency losses and visual prototype loss. The logit-level consistency losses are used to make learnable features close to zero-shot features. The prototype loss makes the visual features approach to the corresponding prototypes in distance. We demonstrate the effectiveness of our method by performing few-shot classification experiments on different datasets including desktop objects. The relevant code will be available at \u0000<uri>https://github.com/NeuCV-IRMI/proclip</uri>\u0000.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Fabry-Perot Interferometer Sensor Based on a Microsphere Tellurite Fiber Probe for Temperature and Hydraulic Pressure Measurement 基于微球碲纤维探针的法布里-珀罗干涉仪传感器，用于温度和水压测量

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-23 DOI: 10.1109/TIM.2024.3485459

Deyuan Zhong;Yuhan Qu;Qi Wang;Xue Zhou;Xin Yan;Tonglei Cheng

{"title":"A Fabry-Perot Interferometer Sensor Based on a Microsphere Tellurite Fiber Probe for Temperature and Hydraulic Pressure Measurement","authors":"Deyuan Zhong;Yuhan Qu;Qi Wang;Xue Zhou;Xin Yan;Tonglei Cheng","doi":"10.1109/TIM.2024.3485459","DOIUrl":"https://doi.org/10.1109/TIM.2024.3485459","url":null,"abstract":"In this article, a tellurite fiber (TF) was fabricated into a microsphere structure via discharge and sequentially coupled with a multimode fiber and a single-mode fiber (SMF) to form a Fabry-Perot interferometer (FPI) sensor. Changes in temperature and hydraulic pressure cause the microsphere to deform, altering the interference length of reflected lights and establishing their dependency relationship. Experimental results showed that the proposed FPI sensor had temperature sensitivity of 157 pm/°C and hydraulic pressure sensitivity of 11.4 pm/MPa. In addition, repetitive experiments and stability tests were conducted, and the maximum relative standard deviation (RSD) was calculated to be \u0000<inline-formula> <tex-math>$4.34times 10^{-4}$ </tex-math></inline-formula>\u0000 for temperature and \u0000<inline-formula> <tex-math>$4.48times 10^{-4}$ </tex-math></inline-formula>\u0000 for hydra- ulic pressure. This FPI sensor is characterized by small size, compact structure, high sensitivity, long-term accuracy, and good stability and repeatability. All these features render it suitable for real-time temperature and hydraulic pressure monitoring in complex environments. In addition, the tellurite compositions can be adjusted to help adapt the FPI sensor to specific external environmental conditions, which provides valuable theoretical and technical insights for the development of high-performance sensing devices.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Five-Axis Continuous Sweep Scanning for Curvature Variable Surfaces 曲率可变表面的五轴连续扫描

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-23 DOI: 10.1109/TIM.2024.3485402

Zherun Li;Yijun Shen;Wenze Zhang;Nuodi Huang;Limin Zhu;Yang Zhang

{"title":"Five-Axis Continuous Sweep Scanning for Curvature Variable Surfaces","authors":"Zherun Li;Yijun Shen;Wenze Zhang;Nuodi Huang;Limin Zhu;Yang Zhang","doi":"10.1109/TIM.2024.3485402","DOIUrl":"https://doi.org/10.1109/TIM.2024.3485402","url":null,"abstract":"Curvature variable surfaces have an extensive application in a multitude of products, such as aeroblades. The aeroblade is an essential part of the aviation industry. The rapid inspection of complex aeroblade is crucial to aviation engine production and maintenance. As an emerging inspection technique, five-axis sweep scanning could achieve higher inspection efficiency compared to the traditional point-by-point probing and line scanning inspection. However, for surfaces with significant curvature variation, such as the blade cross section, the existing five-axis sweep scanning methods require the surface to be separated into patches and conduct inspection on each patch. This type of work pattern necessitates a transition move between each patch, which increases the inspection time and decreases the overall inspection efficiency. In this article, a probe-surface force model is proposed to facilitate the selection of stylus orientations, and an iterative algorithm is introduced to determine the optimal stylus orientations. The guiding curve and the probe head trajectory are synchronized using the dual nonuniform rational basis spline (NURBS) method, which settles the path generation failure at the high curvature region. The proposed method can generate a continuous five-axis sweep scanning path for a blade cross section without transition moves, which drastically boosts the inspection efficiency. Blade cross section inspection experiments are conducted using the proposed method, the patch-wise inspection method, and the line scanning inspection method. The experimental results show that the proposed method maintains the same level of inspection accuracy as both the patch-wise method and the line scanning method. Moreover, the proposed method has achieved a reduction in inspection time of 70.71% over the patch-wise method and 84.98% over the line scanning method, thereby validating its effectiveness.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling and Characterization of LiDAR Echo-Waveforms in Fog With Experiment Validations 雾中激光雷达回波波形的建模和特性分析及实验验证

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2024-10-23 DOI: 10.1109/TIM.2024.3485431

Ruiqin Yu;Xiaolu Li;Tengfei Bi;Tao Zhang;Zongyu Liu;Landa Gao;Lijun Xu

{"title":"Modeling and Characterization of LiDAR Echo-Waveforms in Fog With Experiment Validations","authors":"Ruiqin Yu;Xiaolu Li;Tengfei Bi;Tao Zhang;Zongyu Liu;Landa Gao;Lijun Xu","doi":"10.1109/TIM.2024.3485431","DOIUrl":"https://doi.org/10.1109/TIM.2024.3485431","url":null,"abstract":"Light detection and ranging (LiDAR) generates undesirable clutter signals in fog, impeding target recognition ability. To identify fog clutter waveforms, a comprehensive LiDAR echo waveform generation model is established based on the mechanism of photon random movement, involving factors of environmental particle state, systematic parameters, and target characteristics. The emitted-and-returned photon bundle’s random motions are innovatively described as the superposition of multiple random scattering, and analytical formulations are deduced for photon bundle reception probability, guaranteeing both model accuracy and computational efficiency. Validation experiments are conducted in a large-scale fog chamber. The R-squared values between echo waveforms estimated from our model and measured data achieve \u0000<inline-formula> <tex-math>$0.8307sim 0.9754$ </tex-math></inline-formula>\u0000 for fog clutter, and \u0000<inline-formula> <tex-math>$0.9522sim 0.9778$ </tex-math></inline-formula>\u0000 for target, outperforming the contrasting models. In the simulation model and measurement, fog clutter waveforms exhibit right-skewed asymmetric patterns, enabling their easy differentiation from the Gaussian-distributed target echoes. The presented model and results can be expanded to analyze various atmospheric conditions, broadening the application scenarios of LiDAR.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0