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Comparison of the Precipitation Measurement Radar Onboard the FY-3G Meteorological Satellite with Ground-based Radars in China 认领 引用 被引量：2
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作者 Jian SHANG Peng ZHANG +9 位作者 Lei CAO Qiong WU Xiaopeng WANG Xiaowen ZHANG Bosen JIANG Honggang YIN Mei YUAN Da LIU Yubao CHEN Songyan GU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第3期645-660,共16页
China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the qua... China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the quantitative measurement ability of the PMR is critical.China operates more than 250 weather radars over the mainland.Consistency of the spaceborne radar with ground-based radars will enhance precipitation measurement ability,especially over oceans and mountains where observations are sparse.Additionally,the spaceborne radar can be used to evaluate the spatial and temporal homogeneity of the ground-based radar network.This paper focuses on comparing the PMR onboard the FY-3G satellite with S-band China New Generation Weather Radars(CINRADs).A comparison algorithm between the PMR and CINRADs has been developed,incorporating detailed quality control,attenuation correction,data optimization,spatiotemporal matching,non-uniform beam filling constraint,uniformity constraint,and frequency correction.The matched data in typical months of four seasons were selected to carry out the comparison.The data consistency between the PMR and CINRADs was analyzed.The correlation coefficient is 0.87,the deviation is 0.89 dB,and the standard deviation is 2.50 dB,based on 98226 matching samples.The results show the radar reflectivity of the PMR is quite comparable to that of the CINRADs,demonstrating that the PMR data quality is satisfactory and can be used to verify and correct data consistency among multiple ground-based radars.This work also paves the way for data fusion and joint application of satellite and ground radars in the future. 展开更多
关键词 precipitation radar comparison validation FY-3G weather radar
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Geostationary Satellite–Based Proxy Radar Observations:Expanding Coverage for Storm Tracking 认领 引用 被引量：1
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作者 Yunheng XUE Mengxue XU +4 位作者 Jun LI Bo LI Min MIN Peng ZHANG Ling YANG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第2期307-320,共14页
Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostation... Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostationary(GEO)weather satellites provide continuous observations with seamless coverage with advanced imager, despite their limited capability to penetrate clouds. Combining satellite and ground-radar observations could exploit the advantages of both techniques, providing tracking capability close to that of ground radar while maintaining full spatial coverage. This study presents a novel method called Multi-dimensional satellite Observation information for Radar Estimation(MORE) to reconstruct radar composite reflectivity(CREF). Deep learning techniques are important components of MORE for estimating CREF from China's Fengyun-4B(FY-4B) GEO satellite observations. Two models are developed: an infraredonly(IR-Single) model available for all times, and a visible-infrared(VIS+IR) model for daytime applications. These models incorporate multi-dimensional satellite observation information, including temporal, spatial, spectral, and viewing angle information, to enhance the accuracy of radar echo reconstruction. Results demonstrate that the VIS+IR model outperforms the IR-Single model, and both models achieves a root-mean-square error(RMSE) of less than 6 dBZ and a coefficient of determination(R~2) of greater than 0.7. The models effectively reconstruct radar echoes, including strong echoes exceeding 50 dBZ, and show good agreement with precipitation data in radar-blind areas. This study offers a valuable solution for severe weather monitoring and tracking in regions lacking ground-based radar observations, and provides a potential tool for enhanced data assimilation in numerical weather prediction(NWP) models. 展开更多
关键词 radar composite reflectivity FY-4B deep learning severe weather
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Research on Vehicle Joint Radar Communication Resource Optimization Method Based on GNN-DRL 认领 引用 被引量：1
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作者 Zeyu Chen Jian Sun +1 位作者 Zhengda Huan Ziyi Zhang 《Computers, Materials & Continua》 SCIE EI 2026年第2期1430-1446,共17页
To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framewor... To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framework integrating Deep Reinforcement Learning(DRL)and Graph Neural Network(GNN)is proposed.This framework models resource allocation as a Partially Observable Markov Game(POMG),designs a weighted reward function to balance radar and communication efficiencies,adopts the Multi-Agent Proximal Policy Optimization(MAPPO)framework,and integrates Graph Convolutional Networks(GCN)and Graph Sample and Aggregate(Graph-SAGE)to optimize information interaction.Simulations show that,compared with traditional methods and pure DRL methods,the proposed framework achieves improvements in performance metrics such as communication success rate,Average Age of Information(AoI),and policy convergence speed,effectively enabling resource management in complex environments.Moreover,the proposed GNN-DRL-based intelligent optimization framework obtains significantly better performance for resource management in multi-agent JRC systems than traditional methods and pure DRL methods. 展开更多
关键词 Graph neural network joint radar and communication resource allocation multi-agent collaboration
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Joint multi-dimensional resource scheduling for cooperative tracking of multiple LEO targets via space-based radar networks 认领 引用 被引量：1
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作者 Qingwei YANG Libing JIANG +2 位作者 Shuyu ZHENG Yingjian ZHAO Zhuang WANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第4期449-466,共18页
Appropriate resource scheduling is the key to achieving the best performance of Low Earth-Orbit(LEO)Multi-Target Tracking(MTT)for the Space-based Radar Networks(SBRN)system.The high-velocity nature of satellites impos... Appropriate resource scheduling is the key to achieving the best performance of Low Earth-Orbit(LEO)Multi-Target Tracking(MTT)for the Space-based Radar Networks(SBRN)system.The high-velocity nature of satellites imposes high demands on the convergence rate of filtering and tracking accuracy while escalating the complexity of dynamic scheduling.To address these challenges,this paper utilizes Two-Line Elements(TLE)information to fully exploit the limited power-aperture resource of space-based Colocated Multiple-Input Multiple-Output(C-MIMO)radar and constructs a Walker constellation SBRN system.On this basis,a cognitive distributed cooperative tracking framework with fusion feedback mechanism is proposed.Each node can serve as the fusion center,achieving optimal fusion through the Fast Covariance Intersection(FCI)criterion while reducing the communication requirements.The global outcomes are fed back to all local nodes which can hasten the convergence rate of target state estimation.To maximize the global MTT performance,a closed-loop Joint Multi-Dimensional Resource Scheduling(JMDRS)strategy that considers multi-coverage conditions and visible windows is established.Moreover,the Posterior Cramer-Rao Lower Bound under Global Fusion Feedback(GF-PCRLB)is derived to provide a quantifiable metric for the overall performance.Finally,a fast suboptimal solution to the nonconvex model is proposed based on cross-iterative dimension reduction and variable decoupling.It introduces the tracking Efficiency-to-Cost Ratio(ECR)to jointly decide the beam pointing as well as the transmit power and fusion weight of each beam.Numerical results demonstrate that the proposed method significantly outperforms the existing approaches in enhancing the MTT performance of the SBRN system. 展开更多
关键词 Dynamic resource allocation Moving platform cooperative tracking Multi-Target Tracking(MTT) Space-based Radar Networks(SBRN) Task management
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Experimental techniques for qualitative and quantitative characterization of shale oil reservoir space,minerals,and fluids 认领 引用 被引量：1
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作者 Siyu Chen Zhenkai Huang +6 位作者 Guangyou Zhu Xi Li Zhiyong Chen Ruilin Wang Yue Huang Shengnan Liu Bijun Huang 《Energy Geoscience》 EI CAS CSCD 2026年第2期1-16,共16页
Characterizing shale oil reservoirs encompassing pore space,mineralogy,and fluids is fundamental to effective exploration and development.Recent advances in experimental techniques have significantly improved both the... Characterizing shale oil reservoirs encompassing pore space,mineralogy,and fluids is fundamental to effective exploration and development.Recent advances in experimental techniques have significantly improved both the qualitative and quantitative analysis of these components;however,a comprehensive systematic review is lacking.High-resolution imaging technologies,such as Scanning Electron Microscopy(SEM),Field Emission Scanning Electron Microscopy(FE-SEM),and Focused Ion Beam Scanning Electron Microscopy(FIB-SEM),enable detailed visualization of pore structures.Gas adsorption and high-pressure mercury intrusion methods provide accurate pore-scale quantification.Moreover,techniques like X-ray Diffraction(XRD),X-ray Fluorescence Spectroscopy(XRF),and Electron Probe Microanalysis(EPMA)allow precise mineral identification and compositional analysis.Confocal Scanning Laser Microscopy(CSLM),Raman Spectroscopy,Nuclear Magnetic Resonance(NMR),and Rock Pyrolysis provide insights into fluid occurrence and content within shale reservoirs.Based on a comprehensive review of existing research,this study identifies several key future directions:(1)addressing the challenges of nanopore observation in reservoir space characterization while minimizing the impact of sample preparation on pore structure;(2)improving the accuracy of quantitative mineral analysis and developing advanced new technologies for the precise measurement of complex mineral compositions;(3)enhancing the fluid quantitative evaluation of fluids by more effectively restoring subsurface geological conditions.This paper presents a current synthesis and forward-looking perspective on experimental techniques supporting shale oil exploration,aiming to guide future research and technological innovation in this field. 展开更多
关键词 Experimental technique Shale oil Reservoir space Mineral analysis Fluid characterization Qualitative and quantitative analysis
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Collaborative Assessment of Reflectivity Consistency between FY-3G Precipitation Measurement Radar and Ground-Based Radars 认领 引用
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作者 Chunyan ZHANG Heng HU +4 位作者 Jiashan ZHU Qinqiang ZHOU Lei WU Jianyong LI Xuan ZHU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第5期1065-1078,共14页
FY-3G is the first polar-orbiting satellite equipped with a precipitation measurement radar(PMR)operating at Ku-andKa-band frequencies in China.In this study,we compare the reflectivity data from the FY-3G PMR Ku prod... FY-3G is the first polar-orbiting satellite equipped with a precipitation measurement radar(PMR)operating at Ku-andKa-band frequencies in China.In this study,we compare the reflectivity data from the FY-3G PMR Ku product and groundbasedradars(GRs)during 2024.Also,the FY-3G PMR is used as a third-party reference to evaluate the reflectivityconsistency among different GRs.The FY-3G PMR and GRs share similarities in their general distribution,characteristics,and intensity of reflectivity in strong precipitation cloud systems,though the former presents less detailed system structure.Systematic deviations between the FY-3G PMR and GRs and between GRs are comparable,albeit the reflectivity of the FY-3G PMR is generally slightly stronger than that of GRs(especially X-band GRs),with a mean bias ranging from 0.7 to 1.7dB.S-band GRs exhibit the smallest systematic deviation(STD=3.09 dB)from the FY-3G PMR,whereas the X-band GRsshow the largest(STD=3.61 dB),indirectly indicating the highest internal consistency among S-band GRs and the lowestamong X-band GRs.Besides,both S-and C-band GRs display similar deviations when paired with the FY-3G PMR as wellas when paired with their adjacent S/C-band GRs,suggesting good consistency between these two bands.In contrast,XbandGRs exhibit relatively poor consistency with S-band GRs and the FY-3G PMR,showing a deviation ranging from 3.0to 4.6 dB. 展开更多
关键词 reflectivity deviation consistency FY-3G PMR ground-based radars
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A comprehensive evaluation of non-destructive density and moisture content measurement of asphalt pavement during construction using ground-penetrating radar 认领 引用
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作者 Siqi Wang Mingqi Yang +3 位作者 Yixiang Zhang Xiaoming Huang Tao Ma Dan Wang 《Journal of Road Engineering》 EI CAS 2026年第1期51-73,共23页
In situ density and moisture content of asphalt pavement are essential controlling parameters that require accurate measurement for quality control and quality assurance purposes.The ground-penetrating radar(GPR)techn... In situ density and moisture content of asphalt pavement are essential controlling parameters that require accurate measurement for quality control and quality assurance purposes.The ground-penetrating radar(GPR)technique could provide non-destructive,non-contact,and full-coverage estimations of pavement density and moisture content.However,the technical readiness and drawbacks,including prediction models,signal processing algorithms,and testing hardware,remain unclear for agencies and construction practitioners,impeding large-scale implementations.This paper aims to provide a thorough review of the theoretical background and current practices of using GPR for non-destructive measurements of asphalt pavement density and moisture content during construction,thereby allowing for real-time correction of over-or under-compaction on site.The principles and applications of GPR-based density and moisture content prediction models were comprehensively summarized.Their strengths and limitations were discussed.Cutting-edge GPR equipment suitable for such applications was introduced,including their system components,application scenarios,and inherent limitations.Factors affecting prediction accuracy were analyzed.Advanced signal processing algorithms were discussed in the end,along with the in-place calibration procedure for aggregate dielectric constants.The reviewed technique could be a guiding tool for real-time monitoring of asphalt pavement density and moisture content using GPR,offering practical insights for future development and standardized deployment in construction quality management. 展开更多
关键词 Asphalt pavement Ground-penetrating radar Intelligent compaction Non-destructive testing
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A numerical study on polarization-dependent X-band marine radar backscatter at low grazing angles 认领 引用
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作者 Zhongbiao Chen Runxia Sun +1 位作者 Yijun He Xue Feng 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2026年第3期162-173,共12页
Although X-band marine radar has been used to observe sea surface wave parameters,the underlying scattering mechanisms at low grazing angles remain incompletely understood,which limits its practical applicability.To s... Although X-band marine radar has been used to observe sea surface wave parameters,the underlying scattering mechanisms at low grazing angles remain incompletely understood,which limits its practical applicability.To study the mechanisms,a range-resolved numerical approach that integrates hydrodynamic wave simulation with electromagnetic scattering calculations is developed.First,two numerical wave tanks are implemented using Open FOAM:tankⅠsimulates first-order Stokes waves with varying steepness,while tankⅡmodels incipient wave breaking over a sloping seabed.Second,the Method of Moments is employed to compute the radar backscatter from each point on the simulated wave surfaces.The simulated radar backscatter agrees well with the gray-value variations observed by X-band marine radars in a field experiment.Specifically,HH-polarized returns exhibit two comparable peaks near each wave crest,whereas VV-polarized returns show a dominant peak accompanied by a smaller secondary peak;the wavenumber spectrum of VV polarization matches the true wave spectrum,while that of HH polarization displays a broader energy distribution with stronger high-frequency components.As the radius of curvature of the wave crest decreases,the splitting in the gray-value profile becomes more pronounced,underscoring the role of crest geometry in polarizationdependent backscatter mechanisms at low grazing angles.This understanding may help improve methods for retrieving wave parameters from X-band marine radar images. 展开更多
关键词 X-band marine radar sea surface wave low grazing angles scattering mechanism
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OSCJC:An open-set compound jamming cognition method for radar systems in high-intensity electromagnetic warfare 认领 引用
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作者 Kaixiang Zhang Jiaxiang Zhang +3 位作者 Xinrui Han Yilin Wang Bo Wang Quanhua Liu 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第1期436-455,共20页
In high-intensity electromagnetic warfare,radar systems are persistently subjected to multi-jammer attacks,including potentially novel unknown jamming types that may emerge exclusively under wartime conditions.These j... In high-intensity electromagnetic warfare,radar systems are persistently subjected to multi-jammer attacks,including potentially novel unknown jamming types that may emerge exclusively under wartime conditions.These jamming signals severely degrade radar detection performance.Precise recognition of these unknown and compound jamming signals is critical to enhancing the anti-jamming capabilities and overall reliability of radar systems.To address this challenge,this article proposes a novel open-set compound jamming cognition(OSCJC)method.The proposed method employs a detection-classification dual-network architecture,which not only overcomes the false alarm and misdetection issues of traditional closed-set recognition methods when dealing with unknown jamming but also effectively addresses the performance bottleneck of existing open-set recognition techniques focusing on single jamming scenarios in compound jamming environments.To achieve unknown jamming detection,we first employ a consistency labeling strategy to train the detection network using diverse known jamming samples.This strategy enables the network to acquire highly generalizable jamming features,thereby accurately localizing candidate regions for individual jamming components within compound jamming.Subsequently,we introduce contrastive learning to optimize the classification network,significantly enhancing both intra-class clustering and inter-class separability in the jamming feature space.This method not only improves the recognition accuracy of the classification network for known jamming types but also enhances its sensitivity to unknown jamming types.Simulations and experimental data are used to verify the effectiveness of the proposed OSCJC method.Compared with the state-of-the-art open-set recognition methods,the proposed method demonstrates superior recognition accuracy and enhanced environmental adaptability. 展开更多
关键词 Radar compound jamming cognition Open-set recognition Detection-classification dual-network Time-frequency analysis Contrastive learning
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Arbitrary frequency multiplication reconfigurable radar with a lithium niobate repetition-ratemodulated frequency comb 认领 引用
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作者 Tao Zhang Yilun Wang +4 位作者 Xing Zou Runlin Miao Yan Chen Ke Yin Tian Jiang 《Advanced Photonics Nexus》 CSCD 2026年第3期139-147,共9页
Robust and high-resolution radars are desirable for emerging applications ranging from the Internet of Everything to autonomous driving.Photonic radars with frequency multiplication have attracted considerable interes... Robust and high-resolution radars are desirable for emerging applications ranging from the Internet of Everything to autonomous driving.Photonic radars with frequency multiplication have attracted considerable interest for providing high frequency,large bandwidth,and immunity to electromagnetic interference.Nevertheless,their wideband reconfigurability has been restricted by limited and fixed multiplication factors,which hinders robust sensing.In this work,we overcome the constraint by implementing a repetition-ratemodulated frequency comb that enables arbitrary frequency multiplication.Key components,including a phase modulator with 0.74 V half-wave voltage and an intensity modulator with 110-GHz bandwidth fabricated on the thin-film lithium niobate(TFLN),enhance radar performance.The transmitter achieves a record-breaking cross-band operation bandwidth(5.95 to 95.2 GHz),corresponding to a tunable multiplication factor range of 1 to 16.The receiver supports optical dechirping across 0 to 110 GHz.System-level ranging demonstrations,using two distinct radar waveforms,achieve centimeter-level(2.6∕3.5 cm)and real-time resolution.We offer a viable solution for next-generation photonic integrated radar using the TFLN platform. 展开更多
关键词 integrated microwave photonics radar detection thin-film lithium niobate wideband reconfigurability frequency comb
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A Comprehensive Literature Review of AI-Driven Application Mapping and Scheduling Techniques for Network-on-Chip Systems 认领 引用
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作者 Naveed Ahmad Muhammad Kaleem +5 位作者 Mourad Elloumi Muhammad Azhar Mushtaq Ahlem Fatnassi Mohd Fazil Anas Bilal Abdulbasit A.Darem 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第1期118-155,共38页
Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance ... Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks. 展开更多
关键词 Application mapping mapping techniques network-on-chip system on chip optimisation
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Quantitative analysis of flow characteristics within tundishes using dye experiments and image processing techniques 认领 引用
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作者 Hao-Jian Duan Ding-Han Li Li-Feng Zhang 《Journal of Iron and Steel Research International》 SCIE EI CSCD 2026年第2期178-192,共15页
Image processing techniques were employed to analyze the ink dispersion process in a tundish water model,providing quantitative parameters to evaluate fluid flow dynamics.Key parameters,including filling time,dead are... Image processing techniques were employed to analyze the ink dispersion process in a tundish water model,providing quantitative parameters to evaluate fluid flow dynamics.Key parameters,including filling time,dead area fraction,area emptying time,peak concentration time,dead concentration fraction,and concentration emptying time,were introduced.Orthogonal tests were conducted to investigate the effects of dam spacing,height,and openings on tundish flow behavior.Results revealed that the dam spacing of 3760 mm yielded the shortest filling and peak concentration time,while the 4760 mm spacing minimized dead area and concentration fractions.Taller dams(620 mm)reduced dead area fractions but extended peak concentration time.Dams with openings demonstrated improved flow dynamics,reducing both dead area and concentration fractions,as well as emptying time.The consistency between dye experiments and residence time distribution experiments highlights the reliability of these parameters for optimizing tundish design and operation. 展开更多
关键词 Tundish Dye experiment Image processing technique Orthogonal test Dam
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Research on a two-step retracking algorithm for reconstructed waveforms of nearshore radar altimeters 认领 引用
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作者 Yongjun Jia Xingwei Jiang +1 位作者 Dan Qin Bo Yuan 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2026年第3期216-231,共16页
To enhance the accuracy of nearshore data products obtained from nadir radar altimeters,we introduce a novel two-step retracking algorithm for reconstructed waveforms.This approach utilizes Empirical Mode Decompositio... To enhance the accuracy of nearshore data products obtained from nadir radar altimeters,we introduce a novel two-step retracking algorithm for reconstructed waveforms.This approach utilizes Empirical Mode Decomposition(EMD)to extract trend information from the trailing edge of the waveform.Reconstructed waveforms are formed by linking the leading and trailing edge trend information.The retracking process consists of two steps:the first step focuses on retracking a segment of the leading edge to obtain 4 crucial a priori parameters.In the second step,retracking incorporates both the leading and trailing edges using the previously acquired a priori information.We tested the algorithm using data from the HY-2B radar altimeter.Results indicate that the proposed two-step retracking algorithm outperforms the Maximum Likelihood Estimation(MLE4)algorithm currently used in the operational processing of the HY-2B radar altimeter,as well as the Adaptive Leading Edge Subwaveform(ALES)algorithm,in terms of significant wave height(SWH)and sea level anomalies(SLA).Specifically,the standard deviation of the difference in SWH is reduced by 14%,and the standard deviation of the difference in SLA is reduced by approximately 18%.The two-step retracking algorithm effectively leverages trailing edge information,reduces the influence of peak noise on the leading edge,and improves both the utilization and accuracy of the waveform retracking. 展开更多
关键词 reconstructed waveforms two-step retracking algorithm radar altimeter HY-2B satellite
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Recent advances in nonlinear optical techniques for metastatic melanoma diagnosis and mechanistic studies 认领 引用
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作者 Yihui Zhou Wei Lu Hyeon Jeong Lee 《Journal of Innovative Optical Health Sciences》 SCIE EI CSCD 2026年第4期95-113,共19页
Melanoma,a highly aggressive form of skin cancer,is characterized by complex metabolic reprogramming that drives its metastatic potential and therapy resistance.While localized melanoma can be treated effectively,meta... Melanoma,a highly aggressive form of skin cancer,is characterized by complex metabolic reprogramming that drives its metastatic potential and therapy resistance.While localized melanoma can be treated effectively,metastatic melanoma remains largely incurable,creating an urgent need for methods enabling early diagnosis and prognosis.In this review,we summarize recent efforts toward addressing these clinical challenges by nonlinear optical techniques,particularly pump-probe microscopy and vibrational spectroscopy,developed for in vivo investigation of key molecular changes in melanoma progression.These techniques enable label-free,real-time imaging of two critical components in melanoma progression:melanin and lipid droplets,respectively,providing unique insights into molecular mechanisms of melanoma progression.Future research directions focus on transforming these imaging techniques to enhance their clinical applicability and further investigation of the metabolic vulnerabilities of melanoma. 展开更多
关键词 Melanoma nonlinear optical techniques pump-probe microscopy vibrational spectroscopy molecular diagnosis
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Noninvasive Radar Sensing Augmented with Machine Learning for Reliable Detection of Motor Imbalance 认领 引用
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作者 Faten S.Alamri Adil Ali Saleem +2 位作者 Muhammad I.Khan Hafeez Ur Rehman Siddiqui Amjad Rehman 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第1期698-726,共29页
Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to instal... Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to installation challenges and measurement artifacts that can compromise accuracy.This study presents a novel radar-based framework for non-contact motor imbalance detection using 24 GHz continuous-wave radar.A dataset of 1802 experimental trials was sourced,covering four imbalance levels(0,10,20,30 g)across varying motor speeds(500–1500 rpm)and load torques(0–3 Nm).Dual-channel in-phase and quadrature radar signals were captured at 10,000 samples per second for 30-s intervals,preserving both amplitude and phase information for analysis.A multi-domain feature extraction methodology captured imbalance signatures in time,frequency,and complex signal domains.From 65 initial features,statistical analysis using Kruskal–Wallis tests identified significant descriptors,and recursive feature elimination with Random Forest reduced the feature set to 20 dimensions,achieving 69%dimensionality reduction without loss of performance.Six machine learning algorithms,Random Forest,Extra Trees Classifier,Extreme Gradient Boosting,Categorical Boosting,Support Vector Machine with radial basis function kernel,and k-Nearest Neighbors were evaluated with grid-search hyperparameter optimization and five-fold cross-validation.The Extra Trees Classifier achieved the best performance with 98.52%test accuracy,98%cross-validation accuracy,and minimal variance,maintaining per-class precision and recall above 97%.Its superior performance is attributed to its randomized split selection and full bootstrapping strategy,which reduce variance and overfitting while effectively capturing the nonlinear feature interactions and non-normal distributions present in the dataset.The model’s average inference time of 70 ms enables near real-time deployment.Comparative analysis demonstrates that the radar-based framework matches or exceeds traditional contact-based methods while eliminating their inherent limitations,providing a robust,scalable,and noninvasive solution for industrial motor condition monitoring,particularly in hazardous or space-constrained environments. 展开更多
关键词 Condition monitoring imbalance detection industrial applications machine learning motor fault diagnosis non-contact sensing radar sensing vibration monitoring
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Cooperative finite transmit-receive antenna selection and power allocation strategy for multi-target CFAR-detection in multisite MIMO radar intelligent group system under external uncertainty 认领 引用
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作者 Cheng QI Junwei XIE +6 位作者 Haowei ZHANG Bo WANG Jinlin ZHANG Weijian LIU Weike FENG Qun ZHANG Rennong YANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期534-552,共19页
Within the domain of Intelligent Group Systems(IGSs),this paper develops a resourceaware multitarget Constant False Alarm Rate(CFAR)detection framework for multisite MIMO radar systems.It underscores the necessity of ... Within the domain of Intelligent Group Systems(IGSs),this paper develops a resourceaware multitarget Constant False Alarm Rate(CFAR)detection framework for multisite MIMO radar systems.It underscores the necessity of managing finite transmit and receive antennas and transmit power systematically to enhance detection performance.To tackle the multidimensional resource optimization challenge,we introduce a Cooperative Transmit-Receive Antenna Selection and Power Allocation(CTRSPA)strategy.It employs a perception-action cycle that incorporates uncertain external support information to optimize worst-case detection performance with multiple targets.First,we derive a closed-form expression that incorporates uncertainty for the noncoherent integration squared-law detection probability using the Neyman-Pearson criterion.Subsequently,a joint optimization model for antenna selection and power allocation in CFAR detection is formulated,incorporating practical radar resource constraints.Mathematically,this represents an NPhard problem involving coupled continuous and Boolean variables.We propose a three-stage method—Reformulation,Node Picker,and Convex Power Allocation—that capitalizes on the independent convexity of the optimization model for each variable,ensuring a near-optimal result.Simulations confirm the approach's effectiveness,efficiency,and timeliness,particularly for large-scale radar networks,and reveal the impact of threat levels,system layout,and detection parameters on resource allocation. 展开更多
关键词 Combinatorial optimization Constant False Alarm Rate(CFAR) Intelligent Group System Multisite MIMO radar Resource management Target detection
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Radar Beampattern Gain Maximization for MIMO Integrated Sensing and Communication Systems 认领 引用
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作者 Ren Hong Zhang Ruoyu +2 位作者 Chen Guangyi Lin Xu Wu Wen 《China Communications》 SCIE EI CSCD 2026年第2期268-284,共17页
Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for ... Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system. 展开更多
关键词 integrated sensing and communication multiple-input multiple-output performance tradeoff radar beampattern gain semidefinite relaxation
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Synaptic pruning mechanisms and application of emerging imaging techniques in neurological disorders 认领 引用
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作者 Yakang Xing Yi Mo +1 位作者 Qihui Chen Xiao Li 《Neural Regeneration Research》 SCIE CAS CSCD 2026年第5期1698-1714,共17页
Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience... Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders. 展开更多
关键词 chemokine complement experience-dependent driven synaptic pruning imaging techniques neuroglia signaling pathways synapse elimination synaptic pruning
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Pseudo-spectrum based track-before-detect for bistatic radar network 认领 引用
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作者 HAN Tao ZHOU Gongjian 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2026年第1期127-136,共10页
This paper addresses weak target detection problem for bistatic radar via a pseudo-spectrum(PS)based track-before-detect(TBD).Generally,PS-TBD estimates target position and velocity by means of pseudo-spectrum constru... This paper addresses weak target detection problem for bistatic radar via a pseudo-spectrum(PS)based track-before-detect(TBD).Generally,PS-TBD estimates target position and velocity by means of pseudo-spectrum construction in the discrete measurement space and accurate energy accumulation in mixed coordinates.However,the grids within the polar sensing region of the receivers in the bistatic radar are not aligned.Traditional PS-TBD can not directly process these measurements.In this paper,a PS-TBD method for bistatic radar is proposed to overcome this problem.Each cell in the measurement space of the receivers is mapped to the aligned Cartesian coordinates and predicted to the integration frame according to the assumed filter velocity.A PS is formulated centered on the predicted Cartesian position.Then the samples of the pseudo-spectra are accumulated to the nearest cell around the predicted Cartesian position.The procedure of the energy integration is derived in detail.Simulation results validate the efficacy of the proposed method in terms of detection accuracy and parameter estimation. 展开更多
关键词 bistatic radar track-before-detect(TBD) weak target detection pseudo-spectrum(PS)
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An Improved YOLOv11-Based Detection Method for Hidden Void and Loose Defects in Urban Road Ground-Penetrating Radar Images 认领 引用
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作者 Bin Chen Chao Qiu Wanli Cui 《Structural Durability & Health Monitoring》 EI 2026年第4期222-245,共24页
Ground-penetrating radar(GPR)imaging is widely used for detecting hidden defects in urban roads.However,the complex noise environment,large-scale variations in defect features,and the sensitivity of slender defects to... Ground-penetrating radar(GPR)imaging is widely used for detecting hidden defects in urban roads.However,the complex noise environment,large-scale variations in defect features,and the sensitivity of slender defects to annotation errors pose significant challenges to accurate detection.To address these issues,this study proposes an improved object detection framework,termed DFF-MoCA-YOLO,based on YOLOv11 for identifying void and loose defects in GPR images.First,a multi-strategy gated feature fusion module(MSGFF-C3k2)is designed to enhance feature robustness against complex noise and scale variations.Then,aMonte Carlo Attention(MoCAttention)module is introduced to improve defect-feature representation via stochastic sampling and channel recalibration.Subsequently,an adaptive aspect-ratio penalty CIoU loss(CIoU-ARP)is developed to improve bounding box regression accuracy for slender defects.A labeled dataset containing void and loose defects is constructed using multi-source GPR data collected from eight urban roads.Finally,a series of ablation experiments is conducted on the proposed modules.Experimental results demonstrate that the proposed method achieves consistent performance improvements over the baseline YOLOv11 and other mainstream YOLO variants,while maintaining relatively low computational complexity.The results indicate that the proposed framework offers an effective and practical solution for detecting hidden defects in urban roads using GPR images.Moreover,the model’s robustness to noise and ability to accurately detect defects at varying scales make it a promising tool for urban infrastructure maintenance.Its efficient performance with minimal computational overhead makes it suitable for real-time defect detection. 展开更多
关键词 Road hidden defects ground-penetrating radar improvement to YOLOv11
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