IEEE Transactions on Radar Systems最新文献_第9页

Beampattern-Aware Topology and Antenna Pointing Optimization for Distributed Radar Network 分布式雷达网络波束模式感知拓扑与天线指向优化

IF 3.5

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2025-12-30 DOI: 10.1109/TRS.2025.3649715

Kai Guo;Jun Sun;Ye Yuan;Maria Sabrina Greco;Fulvio Gini

{"title":"Beampattern-Aware Topology and Antenna Pointing Optimization for Distributed Radar Network","authors":"Kai Guo;Jun Sun;Ye Yuan;Maria Sabrina Greco;Fulvio Gini","doi":"10.1109/TRS.2025.3649715","DOIUrl":"https://doi.org/10.1109/TRS.2025.3649715","url":null,"abstract":"To enhance the spatial perception capabilities of distributed radar networks (DRNs) in complex environments, this article investigates the coordinated optimization of beampattern-aware topology and antenna pointing for coverage maximization. Unlike prior works that focus exclusively on radar node placement, the proposed framework introduces antenna pointing as an additional optimization dimension, enabling cooperative beam direction adjustment and substantially improving regional coverage. A unified system and signal model is first established, encompassing both transmit and receive channels. Based on this model, we derive the antenna gain for the uniform linear array (ULA) and a detection probability expression that explicitly incorporates antenna pointing effects. Furthermore, a beampattern model is constructed to characterize the influence of pointing errors on radar coverage, and a corresponding quantitative metric is defined to evaluate performance. Leveraging this metric, the coverage maximization problem is formulated as a nonconvex joint optimization over both node positions and antenna orientations. To efficiently solve this high-dimensional problem, an enhanced particle swarm optimization algorithm integrated with the butterfly-optimization-aided particle swarm optimization (BOA-PSO) is adopted, which improves global convergence and search efficiency. Numerical simulations under representative deployment scenarios demonstrate that the proposed method achieves superior coverage and convergence stability, highlighting its potential for practical DRN configuration and resource management.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"296-308"},"PeriodicalIF":3.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148486809","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

Machine Learning-Based Synchronization for Uncoupled Digital Radar Networks 基于机器学习的非耦合数字雷达网络同步

IF 3.5

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-07-16 DOI: 10.1109/TRS.2026.3714051

Julian Aguilar;Lukas Paulus;David Werbunat;Nicolai Kern;Christian Waldschmidt

{"title":"Machine Learning-Based Synchronization for Uncoupled Digital Radar Networks","authors":"Julian Aguilar;Lukas Paulus;David Werbunat;Nicolai Kern;Christian Waldschmidt","doi":"10.1109/TRS.2026.3714051","DOIUrl":"https://doi.org/10.1109/TRS.2026.3714051","url":null,"abstract":"Radar networks offer the possibility to create large virtual apertures with high flexibility. Thus, the achievable angular resolution—a key aspect of many radar-based applications—can be improved beyond that of a single radar sensor. However, coherence between the individual sensor nodes in the network must be established to fully exploit the multistatic information. Especially for uncoupled system topologies, i.e., without distributing reference signals, achieving coherency in time, frequency, and phase poses a significant challenge. Recently, signal processing-based synchronization techniques for uncoupled radar networks have experienced increasing attention. Even though their performance is promising, the computational load and processing time are too demanding for many systems. This article demonstrates a machine learning (ML)-based error estimation approach utilizing standard radar images, e.g., range-Doppler (<inline-formula> <tex-math>$Rv$ </tex-math></inline-formula>) image, range profile (RP), or velocity profile (VP), in combination with a convolutional neural network (CNN). The labor-intensive and costly acquisition of real-life radar data is complemented by a specifically designed simulation framework, capable of generating high-fidelity data. Through various experiments, the CNNs trained on synthetic data demonstrated their estimation accuracy and robustness in comparison to conventional signal processing-based approaches. Finally, the integrated processing chain–combining the proposed ML-based estimation with signal-processing-based correction–is validated using measurement data.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"1318-1333"},"PeriodicalIF":3.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11612832","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626744","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

Platform Heading Adjustment for Target Detection With Shipborne HFSWR Under Constant Moving Speed 恒航速下舰载HFSWR目标检测平台航向调整

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-04-09 DOI: 10.1109/TRS.2026.3682273

Yonggang Ji;Xinran Liu;Menghua Jiang;Jihong Ren;Mingyang Sun;Weifeng Sun;Weimin Huang

{"title":"Platform Heading Adjustment for Target Detection With Shipborne HFSWR Under Constant Moving Speed","authors":"Yonggang Ji;Xinran Liu;Menghua Jiang;Jihong Ren;Mingyang Sun;Weifeng Sun;Weimin Huang","doi":"10.1109/TRS.2026.3682273","DOIUrl":"https://doi.org/10.1109/TRS.2026.3682273","url":null,"abstract":"Shipborne high-frequency surface wave radar (HFSWR) exhibits flexibility in detecting maritime vessel targets. However, the motion of the platform leads to an expansion of the sea clutter blind zone, which can obscure targets and degrade detection performance. Since platform motion is inherent and difficult to eliminate entirely, this article attempts to adjust it to enhance target detection. First, the impact of platform motion on target detection capability is analyzed. Consequently, a platform motion adjustment scheme is proposed, in which target detectability is ensured in both the range-Doppler (RD) coordinate system and the latitude-longitude coordinate system. Furthermore, for the case with constant platform speed, a platform heading adjustment method is developed. Specifically, a genetic algorithm (GA) is applied for global optimization associated with the platform heading adjustment problem for short-duration target tracking cases, while a sequential quadratic programming (SQP) algorithm is employed for local optimization in long-duration scenarios. Simulation and field test results demonstrate that, under the constraint that the sea clutter blind zone broadening cannot be reduced, the proposed method can rapidly shift targets out of the blind zone while effectively preventing targets from falling into the blind zone.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"799-813"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147737077","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

Augmenting Smoke Detection Systems via Radar and Deep Learning for Continuous Hazard and Condition Monitoring: A Multispectral Analysis 通过雷达和深度学习增强烟雾探测系统用于持续危害和状态监测：多光谱分析

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-04-09 DOI: 10.1109/TRS.2026.3682428

Robin Schmitz;Francesca Schenkel;Tobias Körner;Thorsten Schultze;Christoph Baer;Jan C. Balzer;Jan Barowski;Ilona Rolfes;Christian Schulz

{"title":"Augmenting Smoke Detection Systems via Radar and Deep Learning for Continuous Hazard and Condition Monitoring: A Multispectral Analysis","authors":"Robin Schmitz;Francesca Schenkel;Tobias Körner;Thorsten Schultze;Christoph Baer;Jan C. Balzer;Jan Barowski;Ilona Rolfes;Christian Schulz","doi":"10.1109/TRS.2026.3682428","DOIUrl":"https://doi.org/10.1109/TRS.2026.3682428","url":null,"abstract":"Traditional smoke detection systems share inherent limitations. Inter alia, these systems are fundamentally limited by their purely reactive and nonpredictive operation. The objective of this contribution is to extend the advantageous probing capabilities of radar systems toward the augmentation of traditional smoke detectors for continuous condition and hazard monitoring. The particular emphasis is placed here on early stage hazards and critical precursor conditions for preventive fire safety. To this end, static-target radar echoes are classified using deep learning (DL) methods by extracting characteristic patterns caused by subtle changes in the surrounding medium (e.g., water vapor). Measurements were conducted employing ultrawideband frequency-modulated continuous-wave (FMCW) radar systems operating from 80 to 240 GHz, in a controlled indoor proof-of-concept setup, enabling a systematic multispectral analysis. Several scenarios representative of domestic settings were considered, including the frying of a burger patty (BP) (UL 268 standard). The proposed concept achieves classification accuracies of more than 90%, even under strong restrictions. The developed models remain lightweight and fast, well-suited for embedded implementations.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"787-798"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11478517","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147737141","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

A Novel Approach for Automatic Hyperbola Detection and Velocity Estimation in Noisy GPR Data 噪声GPR数据中双曲线自动检测与速度估计的新方法

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-03-30 DOI: 10.1109/TRS.2026.3679229

Swarna Laxmi Panda;Rohit Kumar Karnena;Subrata Maiti;Upendra Kumar Sahoo

{"title":"A Novel Approach for Automatic Hyperbola Detection and Velocity Estimation in Noisy GPR Data","authors":"Swarna Laxmi Panda;Rohit Kumar Karnena;Subrata Maiti;Upendra Kumar Sahoo","doi":"10.1109/TRS.2026.3679229","DOIUrl":"https://doi.org/10.1109/TRS.2026.3679229","url":null,"abstract":"Problem of velocity estimation and clutter removal in ground penetrating radar (GPR) data is a long-standing, complicated issue that has not been completely solved. Errors in velocity estimation lead to inaccurate localization of buried objects in GPR images, whereas unwanted clutter primarily causes false alarms and degrades image quality. Over the last 50 years, researchers have tried and tested various types of novel algorithms to solve these major issues in GPR. A recent article confirms that it is possible to estimate the range and velocity with a certain degree of accuracy for the noisy data, and the clutter can be removed up to a certain degree. Hyperbola fitting is one of the key GPR signal processing techniques, which is useful for velocity estimation as well as localization and classification of buried objects. In this work, we have done enhancements in certain techniques in signal processing steps, which help automatic hyperbola detection, velocity estimation, and clutter removal for noisy data. A novel clustering approach based on cross-correlation and gradient continuity is proposed for segmenting and separating hyperbolic signatures. The gradient-based optimization techniques are used for velocity estimation and target localization for both mono-static and bi-static GPR data. The effectiveness of the proposed algorithms is validated on synthetic as well as laboratory-measured data across various complex scenarios. The proposed approach is found to be effective for separating hyperbolic signatures from clutter and also capable of estimating velocity by fitting corrupted hyperbolas.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"730-744"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665432","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 Low-Cost Radar Processing—The Pulse Pair Compression Technique 一种低成本雷达处理技术——脉冲对压缩技术

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-03-04 DOI: 10.1109/TRS.2026.3670555

François Vincent

引用次数: 0

An Enhanced Knowledge-Aided Clutter Compensation Method for Real-Time Processing in Spaceborne Bistatic Radar Systems 星载双基地雷达实时处理中一种增强的知识辅助杂波补偿方法

IF 3.5

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-08-28 DOI: 10.1109/TRS.2026.3728640

Gengze Qin;Jixia Fan;Lingyu Wang;Penghui Huang;Jingtao Ma;Zhiling Liu

{"title":"An Enhanced Knowledge-Aided Clutter Compensation Method for Real-Time Processing in Spaceborne Bistatic Radar Systems","authors":"Gengze Qin;Jixia Fan;Lingyu Wang;Penghui Huang;Jingtao Ma;Zhiling Liu","doi":"10.1109/TRS.2026.3728640","DOIUrl":"https://doi.org/10.1109/TRS.2026.3728640","url":null,"abstract":"Due to the nonideal and asymmetric radar configuration, the clutter echoes in spaceborne multistatic radar systems often exhibit strong range dependence. This phenomenon can significantly reduce the estimation accuracy of the clutter covariance matrix (CCM), thereby degrading the clutter suppression performance and weakening the radar system’s capability in detecting slow-moving targets. To address this issue while satisfying the real-time processing requirements, this article proposes an enhanced knowledge-aided clutter compensation (KAC+) method for real-time processing in spaceborne bistatic radar systems. In the proposed approach, the clutter energy distribution is first approximated as a bistatic antenna pattern. By means of analytical computation, the coordinates of the clutter centroids at different range gates are iteratively calculated, and the corresponding spatial and Doppler frequencies are further derived. Based on this, a 2-D space–time compensation matrix is constructed to correct the range-dependent clutter. Finally, a set of semirealistic simulation experiments and complexity analysis are conducted to validate the effectiveness and computational efficiency of the proposed clutter compensation method.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"1544-1558"},"PeriodicalIF":3.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985607","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

Noncoherent Multisite Radar Systems for Multitarget Tracking and Identification Using Micro-Doppler Signatures 基于微多普勒特征的多目标跟踪与识别非相干多站点雷达系统

IF 3.5

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-09-08 DOI: 10.1109/TRS.2026.3731845

Lang Qin;Mandong Zhang;Wenting Song;Zhiqiang Huang;Xiaoguang Liu

{"title":"Noncoherent Multisite Radar Systems for Multitarget Tracking and Identification Using Micro-Doppler Signatures","authors":"Lang Qin;Mandong Zhang;Wenting Song;Zhiqiang Huang;Xiaoguang Liu","doi":"10.1109/TRS.2026.3731845","DOIUrl":"https://doi.org/10.1109/TRS.2026.3731845","url":null,"abstract":"MmWave radar is a promising sensing modality for noncontact, privacy-preserving human tracking and identification. However, single-radar systems remain limited by spatial-resolution constraints, which often lead to target merging, trajectory fragmentation, and identity discontinuity under close-proximity interactions. To address these limitations, this article proposes a noncoherent dual-radar tracking framework for multitarget tracking and identification. The framework uses two orthogonally deployed noncoherent multiple-input-multiple-output (MIMO) radars to provide complementary range observations for trilateration-based localization. Its main contribution is an event-anchored cross-view association strategy that exploits temporally stable micro-Doppler kinematic-transition events as temporal anchors to establish cross-radar correspondence before trilateration. By linking cross-view micro-Doppler consistency with dual-radar geometric constraints, the proposed method mitigates ghost-target ambiguities in multitarget trilateration. To improve robustness, sequence-level consistency is further enforced for cross-radar event verification and identity-preserving trajectory association. A multitarget human kinematic simulation model is developed for controlled evaluation, and real-world indoor experiments are conducted for validation. Results show that the proposed approach achieves a target identity consistency accuracy (ICA) of 94.0% and a multiobject tracking accuracy (MOTA) of 94.35%. These results demonstrate effective preservation of spatial and temporal continuity in challenging indoor environments.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"1606-1623"},"PeriodicalIF":3.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130816","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

Frequency-Dependent Persistence Representation of Sea Clutter for Maritime Radar Target Detection 海上雷达目标探测中海杂波的频率相关持久性表示

IF 3.5

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-09-29 DOI: 10.1109/TRS.2026.3737882

Zhongshu Li;Zhen Wang;Yuchen Huang;Jun Liu;Chang Chen;Weijian Liu;Weidong Chen

{"title":"Frequency-Dependent Persistence Representation of Sea Clutter for Maritime Radar Target Detection","authors":"Zhongshu Li;Zhen Wang;Yuchen Huang;Jun Liu;Chang Chen;Weijian Liu;Weidong Chen","doi":"10.1109/TRS.2026.3737882","DOIUrl":"https://doi.org/10.1109/TRS.2026.3737882","url":null,"abstract":"In maritime radar target detection, sea-surface backscatter forms a complex clutter background with frequency-dependent temporal persistence and heavy-tailed compound-Gaussian (CG) statistics, which makes weak target detection difficult. To address this problem, this article proposes a frequency-dependent persistence representation with CG clutter constraint, termed FDPR-CG, for maritime target detection from measured sea clutter. The proposed FDPR learns Doppler-dependent temporal supports from clutter-only observations, thereby providing an adaptive representation of sea-surface radar backscatter with different persistence behaviors across the Doppler spectrum. To further account for the heavy-tailed statistics of sea clutter, the reconstructed clutter component is constrained under an inverse-Gamma textured CG (IG-CG) model, which induces a Pareto-type clutter prior in the sparse decomposition formulation. By jointly incorporating frequency-dependent persistence representation and CG statistical modeling, the FDPR-CG improves target-clutter separability and suppresses residual clutter leakage in the extracted target component. Experiments on measured CSIR sea-clutter data with both simulated targets and real maritime targets demonstrate that the proposed method achieves more effective target-clutter separation, stronger clutter leakage suppression, and improved detection performance compared with representative sparse-representation-based methods and classical adaptive detectors.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"1661-1677"},"PeriodicalIF":3.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130921","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

Low-Altitude Wide-Swath Single-Pass SAR Interferometry for UAS-Borne Radar 机载无人机雷达低空宽波段单通SAR干涉测量

IF 3.5

IEEE Transactions on Radar Systems Pub Date : 2026-01-01 Epub Date: 2026-10-09 DOI: 10.1109/TRS.2026.3740490

Marius Widmann;David Werbunat;Alexander Grathwohl;Julian Kanz;Frederik Bormuth;Victor Mustieles-Perez;Christian Waldschmidt

{"title":"Low-Altitude Wide-Swath Single-Pass SAR Interferometry for UAS-Borne Radar","authors":"Marius Widmann;David Werbunat;Alexander Grathwohl;Julian Kanz;Frederik Bormuth;Victor Mustieles-Perez;Christian Waldschmidt","doi":"10.1109/TRS.2026.3740490","DOIUrl":"https://doi.org/10.1109/TRS.2026.3740490","url":null,"abstract":"Synthetic aperture radar (SAR) interferometry based on uncrewed aerial systems (UASs) enables highly flexible and cost-efficient measurements, but the low-altitude flight regime introduces fundamental challenges. Short sensor-to-target ranges require wide antenna beams to achieve sufficient azimuth resolution according to the SAR principle, which in turn induces large angular variations across the synthetic aperture. These variations strongly affect SAR image formation and interferometric coherence, and cannot be reliably handled with conventional processing methods developed for spaceborne or fixed-wing platforms. This article introduces a dedicated signal processing approach specifically tailored to UAS-based single-pass SAR interferometry (InSAR). The method explicitly incorporates the platform’s time-varying geometry and uses backprojection (BP) as the underlying algorithm, providing the flexibility to accommodate nonlinear flight trajectories and a wide range of angles. Surface topography is estimated via phase progression across multiple focusing heights, effectively mitigating the ambiguities and error propagation associated with classical phase unwrapping. A detailed analysis of each stage in the processing pipeline—including raw data handling, SAR image formation, and interferometric phase processing—is presented to highlight the influence of geometric effects. Experimental validation based on single-pass UAS measurement campaigns with a frequency-modulated continuous-wave (FMCW) radar demonstrates the reliable generation of high-resolution digital elevation models (DEMs). The results confirm that the proposed approach remains effective under the challenging low-altitude, wide-swath conditions and is well suited for accurate and robust local-scale topographic monitoring.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"1801-1816"},"PeriodicalIF":3.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149248821","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