To address the challenges of complex fluvial sandbody distribution and difficult remaining oil recovery in mature continental oilfields,this study focuses on key issues in reservoir identification such as ambiguous na...To address the challenges of complex fluvial sandbody distribution and difficult remaining oil recovery in mature continental oilfields,this study focuses on key issues in reservoir identification such as ambiguous narrow-channel boundaries and subdivision of multi-stage superimposed sandbodies.Taking the Upper Cretaceous continental sandstone in the Sazhong Oilfield of the Daqing Placanticline as an example,a technical system integrating OVT high-resolution processing,multi-attribute fusion,and varible-scale inversion was developed to establish a complete workflow from seismic processing to reservoir prediction and remaining oil recovery.The following results are obtained.First,the Offset Vector Tile(OVT)seismic processing technology is extended,for the first time,from fracture imaging to sandbody prediction,in order to address the weak seismic responses from boundaries of narrow and thin sandbodies.A geology-oriented OVT partitioning method is developed to significantly improve the imaging accuracy,enabling identification of channel sandbodies as narrow as 50 m.Second,an amplitude-coherence dual-attribute fusion method is proposed for predicting narrow channel boundaries between wells.Constrained by a sedimentary unit-level sequence chronostratigraphic framework,this method accurately delineates 800-2000 m long subaqueous distributary channels with bifurcation-convergence features.Third,considering the superimposition of multi-stage channels,a three-level variable-scale stratigraphic model(sandstone groups,sublayers,sedimentary units)is constructed to overcome single-scale modeling limitations,successfully characterizing key sedimentary features like meandering river“cut-offs”through 3D seismic inversion.Based on these advances,a direct link between seismic prediction and remaining oil recovery is established.The horizontal wells deployed using narrow-channel predictions encountered oil-bearing sandstones in the horizontal section by 97%,and achieved initial daily production of 12.5 t per well.Precise identification of individual channel boundaries within 17 composite sandbodies guided recovery processes in 135 wells,yielding an average daily increase of 2.8 t per well and a cumulative increase of 13.6×10^(4)t.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
In complex media scattering,multiple scattering severely degrades the optical wavefront and results in blurred images,while the spectral distortion caused by the scattering effect leads to severe color distortion.Achi...In complex media scattering,multiple scattering severely degrades the optical wavefront and results in blurred images,while the spectral distortion caused by the scattering effect leads to severe color distortion.Achieving color high-resolution imaging through scattering media remains a significant challenge.Here,we propose a broadband,polarization-based method for color high-resolution imaging through scattering media.This approach enables high-resolution reconstruction by effectively separating the speckle illumination pattern from the mixed-scattering field information,leveraging polarization common-mode characteristics.Concurrently,it incorporates chromatic balance compensation to correct spectral aliasing in the scattered light field,enabling color high-resolution imaging through complex scattering media.To further optimize color distortion caused by scattering,a compensation strategy combining color constancy and white balance theory is adopted.Experimental results demonstrate that the proposed method significantly enhances both spatial resolution and color fidelity across various scattering conditions and target materials,showcasing strong adaptability and robustness.This approach provides an effective solution for achieving high-resolution color optical imaging in complex scattering environments.展开更多
The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast ...The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast charge leads to the lithium concentration gradient in the solid and electrolyte phases and the non-uniform electrochemical reaction at the solid/electrolyte interface.In order to decouple charge transfer reactions in LIBs under dynamic conditions,understanding the spatio-temporal resolution of the P2D model is urgently required.Till now,the study of this aspect is still insufficient.This work studies the spatio-temporal resolution for dynamic/static electrochemical impedance spectroscopy(DEIS/SEIS)on multiple scales.In detail,DEIS and SEIS with spatio-temporal resolutions are used to decouple charge transfer reactions in LIBs based on the numerical solution of the P2D model in the frequency domain.The calculated results indicate that decoupling solid diffusion requires a high spatial resolution along the r-direction in particles,decoupling electrolyte diffusion and interfacial transfer reaction requires a high spatial resolution along the x-direction,and decoupling charge transfer reactions in LIBs at an extremely low state of charge(SOC)requires an extremely high temporal resolution along the t-direction.Finally,the optimal range of spatio-temporal resolutions for DEIS/SEIS is derived,and the method to decouple charge transfer reactions with spatio-temporal resolutions is developed.展开更多
Nociceptive pain is a cardinal feature of traumatic and inflammatory bone diseases.However,whether and how nociceptors actively regulate the immune response during bone regeneration remains unclear.Here,we found that ...Nociceptive pain is a cardinal feature of traumatic and inflammatory bone diseases.However,whether and how nociceptors actively regulate the immune response during bone regeneration remains unclear.Here,we found that neutrophil-triggered nociceptive ingrowth functioned as negative feedback regulation to inflammation during bone healing.A unique Il4ra^(+)Ccl2^(high) neutrophil subset drove intense postinjury TRPV1^(+)nociceptive ingrowth,which in return dissipated inflammation by activating the production of pro-resolving mediator lipoxin A4(LXA4)in osteoblasts.Mechanistically,osteoblastic autophagy activated by nociceptor-derived calcitonin gene-related peptide(CGRP)suppressed the nuclear translocation of arachidonate 5-lipoxygenase(5-LOX)to favor the LXA4 biosynthesis.Moreover,in alveolar bone from patients with Type Ⅱ diabetes,we found diminished nociceptive innervation correlated with reduced autophagy,increased inflammation,and impaired bone formation.Activating nociceptive nerves by spicy diet or topical administration of a clinical-approved TRPV1 agonist showed therapeutic benefits on alveolar bone healing in diabetic mice.These results reveal a critical neuroimmune interaction underlying the inflammation-regeneration balance during bone repairing and may lead to novel therapeutic strategies for inflammatory bone diseases.展开更多
High-resolution solar observations are critical for resolving small-scale dynamic solar processes.Specifically,solar continuum observations,which are used to characterize the photospheric radiative energy distribution...High-resolution solar observations are critical for resolving small-scale dynamic solar processes.Specifically,solar continuum observations,which are used to characterize the photospheric radiative energy distribution,identify atmospheric temperature gradients,and model space weather events,serve as a cornerstone of solar physics research.However,existing observational frameworks face inherent limitations:space-based instruments are constrained by diffraction limits,while ground-based data suffer from atmospheric turbulence and temporal discontinuity.To address these challenges,this study proposes a resolution enhancement method based on cross-platform data fusion between Solar Dynamics Observatory(SDO)/Helioseismic and Magnetic Imager(HMI)space-based full-disk coverage observations and Optical and Near-infrared Solar Eruption Telescope(ONSET)ground-based high-resolution local observations to overcome the physical limitations faced by single-instrument observations.Using 6537 preprocessed spatiotemporally aligned datasets(from 2022),we achieve sub-pixel registration via the scale-invariant feature transform(SIFT)algorithm and design a lightweight model called Cross-Instrument Super-Resolution(CISR)based on a residual local feature block network,optimized for feature extraction and reconstruction using the smooth L1-loss function.Experimental results demonstrate that CISR achieves a pixel-wise correlation coefficient of 0.946,a peak signal-to-noise ratio(PSNR)of 33.924 dB,and a structural similarity index of 0.855 on the test set,significantly outperforming bicubic interpolation and the Super-Resolution Convolutional Neural Network(SRCNN)baseline model.Qualitative visual assessment verifies the method’s efficacy for HMI continuum data resolution enhancement,with exceptional performance in maintaining both sunspot boundary acuity and granule structural fidelity.This work provides a novel approach for multi-source solar data synergy,with future potential to incorporate physics-driven evaluation metrics to further improve the model generalization.展开更多
In clinical diagnosis,magnetic resonance imaging(MRI)allows different contrast images to be obtained.High-resolution(HR)MRI presents fine anatomical structures,which is important for improving the efficiency of expert...In clinical diagnosis,magnetic resonance imaging(MRI)allows different contrast images to be obtained.High-resolution(HR)MRI presents fine anatomical structures,which is important for improving the efficiency of expert diagnosis and realising smart healthcare.However,due to the cost of scanning equipment and the time required for scanning,obtaining an HR brain MRI is quite challenging.Therefore,to improve the quality of images,reference-based super-resolution technology has come into existence.Nevertheless,the existing methods still have some drawbacks:(1)The advantages of different contrast images are not fully utilised.(2)The slice-by-slice scanning nature of magnetic resonance imaging is not considered.(3)The ability to capture contextual information and to match and fuse multi-scale,multi-contrast features is lacking.In this paper,we propose the multi-slice aware matching and fusion(MSAMF)network,which makes full use of multi-slice reference images information by introducing a multi-slice aware module and multi-scale matching strategy to capture corresponding contextual information in reference features at other scales.To further integrate matching features,a multi-scale fusion mechanism is also designed to progressively fuse multi-scale matching features,thereby generating more detailed super-resolution images.The experimental results support the benefits of our network in enhancing the quality of brain MRI reconstruction.展开更多
Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelengt...Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelength coverage.In this study,we report the development of a push-broom airborne multimodular imaging spectrometer(AMMIS)that spans ultraviolet(UV),visible near-infrared(VNIR),shortwave infrared(SWIR),and thermal infrared(TIR)wavelengths.As an integral part of China's HighResolution Earth Observation Program,AMMIS is intended for civilian applications and for validating key technologies for future spaceborne hyperspectral payloads.It has been mounted on aircraft platforms such as Y-5,Y-12,and XZ-60.Since 2016,AMMIS has been used to perform more than 30 flight campaigns and gather more than 200 TB of hyperspectral data.This study describes the system design,calibration techniques,performance tests,flight campaigns,and applications of the AMMIS.The system integrates UV,VNIR,SWIR,and TIR modules,which can be operated in combination or individually based on the application requirements.Each module includes three spectrometers,utilizing field-of-view(FOV)stitching technology to achieve a 40°FOV,thereby enhancing operational efficiency.We designed advanced optical systems for all modules,particularly for the TIR module,and employed cryogenic optical technology to maintain optical system stability at 100 K.Both laboratory and in-flight calibrations were conducted to improve preprocessing accuracy and produce high-quality hyperspectral data.The AMMIS features more than 1400 spectral bands,with spectral sampling intervals of 0.1 nm for UV,2.4 nm for VNIR,3 nm for SWIR,and 32 nm for TIR.In addition,the instantaneous fields of view(IFoVs)for the four modules were 0.5,0.25,0.5,and 1 mrad,respectively,with the VNIR module achieving an IFoV of 0.125 mrad in the high-spatial-resolution mode.This study reports on land-cover surveys,pollution gas detection,mineral exploration,coastal water detection,and plant investigations conducted using AMMIS,highlighting its excellent performance.Furthermore,we present three hyperspectral datasets with diverse scene distributions and categories suitable for developing artificial intelligence algorithms.This study paves the way for next-generation airborne and spaceborne hyperspectral payloads and serves as a valuable reference for hyperspectral sensor designers and data users.展开更多
Conflict resolution(CR)is a fundamental component of air traffic management,where recent progress in artificial intelligence has led to the effective application of deep reinforcement learning(DRL)techniques to enhanc...Conflict resolution(CR)is a fundamental component of air traffic management,where recent progress in artificial intelligence has led to the effective application of deep reinforcement learning(DRL)techniques to enhance CR strategies.However,existing DRL models applied to CR are often limited to simple scenarios.This approach frequently leads to the neglect of the high risks associated with multiple intersections in the high-density and multi-airport system terminal area(MAS-TMA),and suffers from poor interpretability.This paper addresses the aforementioned gap by introducing an improved multi-agent DRL model that adopted to autonomous CR(AutoCR)within MAS-TMA.Specifically,dynamic weather conditions are incorporated into the state space to enhance adaptability.In the action space,the flight intent is considered and transformed into optimal maneuvers according to overload,thus improving interpretability.On these bases,the deep Q-network(DQN)algorithm is further improved to address the AutoCR problem in MAS-TMA.Simulation experiments conducted in the“Guangdong-Hong Kong-Macao”greater bay area(GBA)MAS-TMA demonstrate the effectiveness of the proposed method,successfully resolving over eight potential conflicts and performing robustly across various air traffic densities.展开更多
We developed an imaging technique combining two-photon computed super-resolution microscopy and suction-based stabilization to achieve the resolution of the single-cell level and organelles in vivo.To accomplish this,...We developed an imaging technique combining two-photon computed super-resolution microscopy and suction-based stabilization to achieve the resolution of the single-cell level and organelles in vivo.To accomplish this,a conventional two-photon microscope was equipped with a 3D-printed holders,which stabilize the tissue surface within the focal plane of immersion objectives.Further computational image stabilization and noise reduction were applied,followed by superresolution radial fluctuations(SRRF)analysis,doubling image resolution,and enhancing signal-to-noise ratios for in vivo subcellular process investigation.Stabilization of<1μm was obtained by suction,and<25 nm were achieved by subsequent algorithmic image stabilization.A Mito-Dendra2 mouse model,expressing green fluorescent protein(GFP)in mitochondria,demonstrated the potential of long-term intravital subcellular imaging.In vivo mitochondrial fission and fusion,mitochondrial status migration,and the effects of alcohol consumption(modeled as an alcoholic liver disease)and berberine treatment on hepatocyte mitochondrial dynamics are directly observed intravitally.Suction-based stabilization in two-photon intravital imaging,coupled with computational super-resolution holds promise for advancing in vivo subcellular imaging studies.展开更多
The parabolic Radon transform has been widely used in multiple attenuation. To further improve the accuracy and efficiency of the Radon transform, we developed the 2- fdomain high-resolution Radon transform based on t...The parabolic Radon transform has been widely used in multiple attenuation. To further improve the accuracy and efficiency of the Radon transform, we developed the 2- fdomain high-resolution Radon transform based on the fast and modified parabolic Radon transform presented by Abbad. The introduction of a new variable 2 makes the transform operator frequency-independent. Thus, we need to calculate the transform operator and its inverse operator only once, which greatly improves the computational efficiency. Besides, because the primaries and multiples are distributed on straight lines with different slopes in the 2-fdomain, we can easily choose the filtering operator to suppress the multiples. At the same time, the proposed method offers the advantage of high-resolution Radon transform, which can greatly improve the precision of attenuating the multiples. Numerical experiments suggest that the multiples are well suppressed and the amplitude versus offset characteristics of the primaries are well maintained. Real data processing results further verify the effectiveness and feasibility of the method.展开更多
Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajec...Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional（4D） Trajectory-Based Operation（4DTBO）, which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CD＆R from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CD＆R scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism（STP） for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.展开更多
For radar high resolution range profile (HRRP) recognition, three aspects are of great importance to improve the performance, i.e. discrimination for outlier, classification for inner and an accurate description for f...For radar high resolution range profile (HRRP) recognition, three aspects are of great importance to improve the performance, i.e. discrimination for outlier, classification for inner and an accurate description for feature space. To tackle these issues, a novel target recognition method is designed, denoted by the multiple support vectors (multi-SV) method. With the proposed method, a special framework is constructed by a treble correlate support vector model to segment the feature space to two regions with the distribution of density, and then the description and classification hyperplane for each region are achieved. Based on the support vector framework, this method needs less memory and computation complexity to fit practical radar HRRP recognition. Finally, the experiment based on the measured data verifies the excellent performance of this method.展开更多
Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-compone...Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-component LFM signal were used by discrete fast fractional Fourier transform （FrFT）. Then the expression of chirp-rate resolution in fractional Fourier domain （FrFD） was deduced from discrete normalize time-frequency distribution, when multi-component LFM signal had only one center frequency. Furthermore, the detail influence of the sampling time, sampling frequency and chirp-rate upon the resolution was analyzed by partial differential equation. Simulation results and analysis indicate that increasing the sampling time can enhance the resolution, but the influence of the sampling frequency can he omitted. What＇s more, in multi-component LFM signal, the chirp-rate resolution of FrFT is no less than a minimal value, and it mainly dependent on the biggest value of chirp-rates, with which it has an approximately positive exponential relationship.展开更多
In the present article, we introduce a high resolution sea surface temperature （SST） product generated daily by Korea Institute of Ocean Science and Technology （KIOST）. The SST product is comprised of four sets of...In the present article, we introduce a high resolution sea surface temperature （SST） product generated daily by Korea Institute of Ocean Science and Technology （KIOST）. The SST product is comprised of four sets of data including eight-hour and daily average SST data of I km resolution, and is based on the four infrared （IR） satellite SST data acquired by advanced very high resolution radiometer （AVHRR）, Moderate Resolution Imaging Spectroradiometer （MODIS）, Multifunctional Transport Satellites-2 （MTSAT-2） Imager and Meteorological Imager （MI）, two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2 （AMSR2）, and WindSAT with in-situ temperature data. These input satellite and in-situ SST data are merged by using the optimal interpolation （OI） algorithm. The root-mean-square-errors （RMSEs） of satellite and in-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from Ianuary to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71~C and the bias value was -0.08~C. The largest RMSE and bias were 0.86 and -0.26~C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Iapan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60~C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature （GHRSST） product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System （KOOS） as an input parameter for data assimilation.展开更多
Orthogonal frequency division multiplexing（OFDM） radar with multicarrier phase-coded waveforms has been recently introduced to achieve high range resolution.The conventional method for obtaining the high resolution ...Orthogonal frequency division multiplexing（OFDM） radar with multicarrier phase-coded waveforms has been recently introduced to achieve high range resolution.The conventional method for obtaining the high resolution range profile（HRRP） is based on matched filters.A method of synthesizing HRRP based on the fast Fourier transform（FFT） and decoding is proposed.The mathematical expressions of HRRP are derived by assuming an elementary scenario of point-scattering targets.Based on the characteristic of OFDM multicarrier signals,it mainly analyzes the influence on HRRP exerted by several factors,such as velocity compensation errors,the sampling frequency offset,and so on.The conclusions are significant for the design of the OFDM imaging radar.Finally,the simulation results demonstrate the validity of the conclusions.展开更多
With the rapid growth of flight flow,the workload of controllers is increasing daily,and handling flight conflicts is the main workload.Therefore,it is necessary to provide more efficient conflict resolution decision-...With the rapid growth of flight flow,the workload of controllers is increasing daily,and handling flight conflicts is the main workload.Therefore,it is necessary to provide more efficient conflict resolution decision-making support for controllers.Due to the limitations of existing methods,they have not been widely used.In this paper,a Deep Reinforcement Learning(DRL)algorithm is proposed to resolve multi-aircraft flight conflict with high solving efficiency.First,the characteristics of multi-aircraft flight conflict problem are analyzed and the problem is modeled based on Markov decision process.Thus,the Independent Deep Q Network(IDQN)algorithm is used to solve the model.Simultaneously,a’downward-compatible’framework that supports dynamic expansion of the number of conflicting aircraft is designed.The model ultimately shows convergence through adequate training.Finally,the test conflict scenarios and indicators were used to verify the validity.In 700 scenarios,85.71%of conflicts were successfully resolved,and 71.51%of aircraft can reach destinations within 150 s around original arrival times.By contrast,conflict resolution algorithm based on DRL has great advantages in solution speed.The method proposed offers the possibility of decision-making support for controllers and reduce workload of controllers in future high-density airspace environment.展开更多
A multi-resolution rectangular shell element with membrane-bending based on the Kirchhoff-Love theory is proposed. The multi-resolution analysis （MRA） framework is formulated out of a mutually nesting displacement s...A multi-resolution rectangular shell element with membrane-bending based on the Kirchhoff-Love theory is proposed. The multi-resolution analysis （MRA） framework is formulated out of a mutually nesting displacement subspace sequence, whose basis functions are constructed of scaling and shifting on the element domain of basic node shape functions. The basic node shape functions are constructed from shifting to other three quadrants around a specific node of a basic element in one quadrant and joining the corresponding node shape functions of four elements at the specific node. The MRA endows the proposed element with the resolution level （RL） to adjust the element node number, thus modulating structural analysis accuracy accordingly. The node shape functions of Kronecker delta property make the treatment of element boundary condition quite convenient and enable the stiffness matrix and the loading column vectors of the proposed element to be automatically acquired through quadraturing around nodes in RL adjusting. As a result, the traditional 4-node rectangular shell element is a mono-resolution one and also a special case of the proposed element. The accuracy of a structural analysis is actually determined by the RL, not by the mesh. The simplicity and clarity of node shape function formulation with the Kronecker delta property, and the rational MRA enable the proposed element method to be implemented more rationally, easily and efficiently than the conventional mono-resolution rectangular shell element method or other corresponding MRA methods.展开更多
Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution...Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution sparse compound-eye camera(CEC)based on dual-end collaborative optimization is proposed,which provides a cost-effective way to break through the trade-off among the field of view,resolution,and imaging speed.In the optical end,a sparse CEC based on liquid lenses is designed,which can realize large-field-of-view imaging in real time,and fast zooming within 5 ms.In the computational end,a disturbed degradation model driven super-resolution network(DDMDSR-Net)is proposed to deal with complex image degradation issues in actual imaging situations,achieving high-robustness and high-fidelity resolution enhancement.Based on the proposed dual-end collaborative optimization framework,the angular resolution of the CEC can be enhanced from 71.6"to 26.0",which provides a solution to realize high-resolution imaging for array camera dispensing with high optical hardware complexity and data transmission bandwidth.Experiments verify the advantages of the CEC based on dual-end collaborative optimization in high-fidelity reconstruction of real scene images,kilometer-level long-distance detection,and dynamic imaging and precise recognition of targets of interest.展开更多
Based on ADS-B surveillance data,this paper proposes a multi-unmanned aerial vehicle(multi-UAV)collision detection method based on linear extrapolation for ground-based UAV collision detection and resolution,thus to p...Based on ADS-B surveillance data,this paper proposes a multi-unmanned aerial vehicle(multi-UAV)collision detection method based on linear extrapolation for ground-based UAV collision detection and resolution,thus to provide early warning of possible conflicts.To address the problem of multi-UAV conflict,the basic ant colony algorithm is introduced.The conflict simplification model of the traditional basic ant colony algorithm is optimized by adding a speed regulation strategy.A multi-UAV conflict resolution scheme is presented based on speed regulation and heading strategies.The ant colony algorithm is improved by adding angle information and a queuing system.The results show that the improved ant colony algorithm can provide multi-UAV joint escape routes for a multi-UAV conflict situation in airspace.Unlike the traditional ant colony algorithm,our approach converges to the optimization target.The time required for the calculation is reduced by 43.9%,and the total delay distance caused by conflict resolution is reduced by 58.4%.展开更多
基金Supported by the China National Science and Technology Major Project(2025ZD1407000)PetroChina Science and Technology Major Project(2023ZZ22)。
文摘To address the challenges of complex fluvial sandbody distribution and difficult remaining oil recovery in mature continental oilfields,this study focuses on key issues in reservoir identification such as ambiguous narrow-channel boundaries and subdivision of multi-stage superimposed sandbodies.Taking the Upper Cretaceous continental sandstone in the Sazhong Oilfield of the Daqing Placanticline as an example,a technical system integrating OVT high-resolution processing,multi-attribute fusion,and varible-scale inversion was developed to establish a complete workflow from seismic processing to reservoir prediction and remaining oil recovery.The following results are obtained.First,the Offset Vector Tile(OVT)seismic processing technology is extended,for the first time,from fracture imaging to sandbody prediction,in order to address the weak seismic responses from boundaries of narrow and thin sandbodies.A geology-oriented OVT partitioning method is developed to significantly improve the imaging accuracy,enabling identification of channel sandbodies as narrow as 50 m.Second,an amplitude-coherence dual-attribute fusion method is proposed for predicting narrow channel boundaries between wells.Constrained by a sedimentary unit-level sequence chronostratigraphic framework,this method accurately delineates 800-2000 m long subaqueous distributary channels with bifurcation-convergence features.Third,considering the superimposition of multi-stage channels,a three-level variable-scale stratigraphic model(sandstone groups,sublayers,sedimentary units)is constructed to overcome single-scale modeling limitations,successfully characterizing key sedimentary features like meandering river“cut-offs”through 3D seismic inversion.Based on these advances,a direct link between seismic prediction and remaining oil recovery is established.The horizontal wells deployed using narrow-channel predictions encountered oil-bearing sandstones in the horizontal section by 97%,and achieved initial daily production of 12.5 t per well.Precise identification of individual channel boundaries within 17 composite sandbodies guided recovery processes in 135 wells,yielding an average daily increase of 2.8 t per well and a cumulative increase of 13.6×10^(4)t.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
基金supported by the National Natural Science Foundation of China (Grant Nos. 62405231, 62405235, and 62575229)the National Key Laboratory of Space Target Awareness (Grant Nos. STA2024KGL0203, STA2024ZCA0203, and STA-24-04-05)+3 种基金the Beijing Key Laboratory of Advanced Optical Remote Sensing Technology (Grant No. AORS202405)the China Postdoctoral Science Foundation (Grant No. 2024M762527)the Shaanxi Province High-level Innovation and Entrepreneurship Talent Program (Grant No. H02439005)the Natural Science Foundation of Shaanxi (Grant Nos. S2024-JC-JCQN-60, S2025-JCQYTS-0107, and 2025JC-QYCX-05)。
文摘In complex media scattering,multiple scattering severely degrades the optical wavefront and results in blurred images,while the spectral distortion caused by the scattering effect leads to severe color distortion.Achieving color high-resolution imaging through scattering media remains a significant challenge.Here,we propose a broadband,polarization-based method for color high-resolution imaging through scattering media.This approach enables high-resolution reconstruction by effectively separating the speckle illumination pattern from the mixed-scattering field information,leveraging polarization common-mode characteristics.Concurrently,it incorporates chromatic balance compensation to correct spectral aliasing in the scattered light field,enabling color high-resolution imaging through complex scattering media.To further optimize color distortion caused by scattering,a compensation strategy combining color constancy and white balance theory is adopted.Experimental results demonstrate that the proposed method significantly enhances both spatial resolution and color fidelity across various scattering conditions and target materials,showcasing strong adaptability and robustness.This approach provides an effective solution for achieving high-resolution color optical imaging in complex scattering environments.
基金supported by the National Natural Science Foundation of China(Nos.22479092 and 22078190)。
文摘The pseudo-two-dimensional(P2D)model plays an important role in exploring physicochemical mechanisms,predicting the state of health,and improving the fast charge capability for Li-ion batteries(LIBs).However,the fast charge leads to the lithium concentration gradient in the solid and electrolyte phases and the non-uniform electrochemical reaction at the solid/electrolyte interface.In order to decouple charge transfer reactions in LIBs under dynamic conditions,understanding the spatio-temporal resolution of the P2D model is urgently required.Till now,the study of this aspect is still insufficient.This work studies the spatio-temporal resolution for dynamic/static electrochemical impedance spectroscopy(DEIS/SEIS)on multiple scales.In detail,DEIS and SEIS with spatio-temporal resolutions are used to decouple charge transfer reactions in LIBs based on the numerical solution of the P2D model in the frequency domain.The calculated results indicate that decoupling solid diffusion requires a high spatial resolution along the r-direction in particles,decoupling electrolyte diffusion and interfacial transfer reaction requires a high spatial resolution along the x-direction,and decoupling charge transfer reactions in LIBs at an extremely low state of charge(SOC)requires an extremely high temporal resolution along the t-direction.Finally,the optimal range of spatio-temporal resolutions for DEIS/SEIS is derived,and the method to decouple charge transfer reactions with spatio-temporal resolutions is developed.
基金The National Natural Science Foundation of China(No.82130027,82301020,82100966)Young Elite Scientists Sponsorship Program by CAST(2024QNRC001)+5 种基金The China Postdoctoral Science Foundation(2023M732283)The National Key Research and Development Program of China(No.2023YFC2413600)The Shanghai Sailing Program(23YF1422000,21YF1424400)Innovative Research Team of High-level Local Universities in Shanghai(SHSMU-ZLCX20212400)Young Elite Scientists Sponsorship Program by CAST(2021QNRC001)Shanghai Pujiang Program(24PJD054).
文摘Nociceptive pain is a cardinal feature of traumatic and inflammatory bone diseases.However,whether and how nociceptors actively regulate the immune response during bone regeneration remains unclear.Here,we found that neutrophil-triggered nociceptive ingrowth functioned as negative feedback regulation to inflammation during bone healing.A unique Il4ra^(+)Ccl2^(high) neutrophil subset drove intense postinjury TRPV1^(+)nociceptive ingrowth,which in return dissipated inflammation by activating the production of pro-resolving mediator lipoxin A4(LXA4)in osteoblasts.Mechanistically,osteoblastic autophagy activated by nociceptor-derived calcitonin gene-related peptide(CGRP)suppressed the nuclear translocation of arachidonate 5-lipoxygenase(5-LOX)to favor the LXA4 biosynthesis.Moreover,in alveolar bone from patients with Type Ⅱ diabetes,we found diminished nociceptive innervation correlated with reduced autophagy,increased inflammation,and impaired bone formation.Activating nociceptive nerves by spicy diet or topical administration of a clinical-approved TRPV1 agonist showed therapeutic benefits on alveolar bone healing in diabetic mice.These results reveal a critical neuroimmune interaction underlying the inflammation-regeneration balance during bone repairing and may lead to novel therapeutic strategies for inflammatory bone diseases.
基金supported by the National Natural Science Foundation of China(12003068)the Yunnan Key Laboratory of Solar Physics and Space Science(202205AG070009).
文摘High-resolution solar observations are critical for resolving small-scale dynamic solar processes.Specifically,solar continuum observations,which are used to characterize the photospheric radiative energy distribution,identify atmospheric temperature gradients,and model space weather events,serve as a cornerstone of solar physics research.However,existing observational frameworks face inherent limitations:space-based instruments are constrained by diffraction limits,while ground-based data suffer from atmospheric turbulence and temporal discontinuity.To address these challenges,this study proposes a resolution enhancement method based on cross-platform data fusion between Solar Dynamics Observatory(SDO)/Helioseismic and Magnetic Imager(HMI)space-based full-disk coverage observations and Optical and Near-infrared Solar Eruption Telescope(ONSET)ground-based high-resolution local observations to overcome the physical limitations faced by single-instrument observations.Using 6537 preprocessed spatiotemporally aligned datasets(from 2022),we achieve sub-pixel registration via the scale-invariant feature transform(SIFT)algorithm and design a lightweight model called Cross-Instrument Super-Resolution(CISR)based on a residual local feature block network,optimized for feature extraction and reconstruction using the smooth L1-loss function.Experimental results demonstrate that CISR achieves a pixel-wise correlation coefficient of 0.946,a peak signal-to-noise ratio(PSNR)of 33.924 dB,and a structural similarity index of 0.855 on the test set,significantly outperforming bicubic interpolation and the Super-Resolution Convolutional Neural Network(SRCNN)baseline model.Qualitative visual assessment verifies the method’s efficacy for HMI continuum data resolution enhancement,with exceptional performance in maintaining both sunspot boundary acuity and granule structural fidelity.This work provides a novel approach for multi-source solar data synergy,with future potential to incorporate physics-driven evaluation metrics to further improve the model generalization.
基金supported by the National Natural Science Foundation of China(Grants 62376184,62206196,62403345,62303445)Shanxi Provincial Special Guidance Program for the Transformation of Scientific and Technological Achievements(Grants 202304021301035,202404021301032)Central Guided Local Science and Technology Development Project(Grant YDZJSX20231A017).
文摘In clinical diagnosis,magnetic resonance imaging(MRI)allows different contrast images to be obtained.High-resolution(HR)MRI presents fine anatomical structures,which is important for improving the efficiency of expert diagnosis and realising smart healthcare.However,due to the cost of scanning equipment and the time required for scanning,obtaining an HR brain MRI is quite challenging.Therefore,to improve the quality of images,reference-based super-resolution technology has come into existence.Nevertheless,the existing methods still have some drawbacks:(1)The advantages of different contrast images are not fully utilised.(2)The slice-by-slice scanning nature of magnetic resonance imaging is not considered.(3)The ability to capture contextual information and to match and fuse multi-scale,multi-contrast features is lacking.In this paper,we propose the multi-slice aware matching and fusion(MSAMF)network,which makes full use of multi-slice reference images information by introducing a multi-slice aware module and multi-scale matching strategy to capture corresponding contextual information in reference features at other scales.To further integrate matching features,a multi-scale fusion mechanism is also designed to progressively fuse multi-scale matching features,thereby generating more detailed super-resolution images.The experimental results support the benefits of our network in enhancing the quality of brain MRI reconstruction.
基金supported by the Shanghai Industrial Collaborative Innovation Fund(HCXBCY-2021-001)the Academy of Finland(349229)。
文摘Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelength coverage.In this study,we report the development of a push-broom airborne multimodular imaging spectrometer(AMMIS)that spans ultraviolet(UV),visible near-infrared(VNIR),shortwave infrared(SWIR),and thermal infrared(TIR)wavelengths.As an integral part of China's HighResolution Earth Observation Program,AMMIS is intended for civilian applications and for validating key technologies for future spaceborne hyperspectral payloads.It has been mounted on aircraft platforms such as Y-5,Y-12,and XZ-60.Since 2016,AMMIS has been used to perform more than 30 flight campaigns and gather more than 200 TB of hyperspectral data.This study describes the system design,calibration techniques,performance tests,flight campaigns,and applications of the AMMIS.The system integrates UV,VNIR,SWIR,and TIR modules,which can be operated in combination or individually based on the application requirements.Each module includes three spectrometers,utilizing field-of-view(FOV)stitching technology to achieve a 40°FOV,thereby enhancing operational efficiency.We designed advanced optical systems for all modules,particularly for the TIR module,and employed cryogenic optical technology to maintain optical system stability at 100 K.Both laboratory and in-flight calibrations were conducted to improve preprocessing accuracy and produce high-quality hyperspectral data.The AMMIS features more than 1400 spectral bands,with spectral sampling intervals of 0.1 nm for UV,2.4 nm for VNIR,3 nm for SWIR,and 32 nm for TIR.In addition,the instantaneous fields of view(IFoVs)for the four modules were 0.5,0.25,0.5,and 1 mrad,respectively,with the VNIR module achieving an IFoV of 0.125 mrad in the high-spatial-resolution mode.This study reports on land-cover surveys,pollution gas detection,mineral exploration,coastal water detection,and plant investigations conducted using AMMIS,highlighting its excellent performance.Furthermore,we present three hyperspectral datasets with diverse scene distributions and categories suitable for developing artificial intelligence algorithms.This study paves the way for next-generation airborne and spaceborne hyperspectral payloads and serves as a valuable reference for hyperspectral sensor designers and data users.
基金supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX25_0621)the Foundation of Inter-disciplinary Innovation Fund for Doctoral Students of Nanjing University of Aeronautics and Astronautics(No.KXKCXJJ202507)。
文摘Conflict resolution(CR)is a fundamental component of air traffic management,where recent progress in artificial intelligence has led to the effective application of deep reinforcement learning(DRL)techniques to enhance CR strategies.However,existing DRL models applied to CR are often limited to simple scenarios.This approach frequently leads to the neglect of the high risks associated with multiple intersections in the high-density and multi-airport system terminal area(MAS-TMA),and suffers from poor interpretability.This paper addresses the aforementioned gap by introducing an improved multi-agent DRL model that adopted to autonomous CR(AutoCR)within MAS-TMA.Specifically,dynamic weather conditions are incorporated into the state space to enhance adaptability.In the action space,the flight intent is considered and transformed into optimal maneuvers according to overload,thus improving interpretability.On these bases,the deep Q-network(DQN)algorithm is further improved to address the AutoCR problem in MAS-TMA.Simulation experiments conducted in the“Guangdong-Hong Kong-Macao”greater bay area(GBA)MAS-TMA demonstrate the effectiveness of the proposed method,successfully resolving over eight potential conflicts and performing robustly across various air traffic densities.
基金supported by the Ministry of Science,ICT and Future Planning(MSIP)through the National Research Foundation of Korea(NRF)(RS-2024-00450201)supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI),funded by the Ministry of Health and Welfare,Republic of Korea(HI22C1374).
文摘We developed an imaging technique combining two-photon computed super-resolution microscopy and suction-based stabilization to achieve the resolution of the single-cell level and organelles in vivo.To accomplish this,a conventional two-photon microscope was equipped with a 3D-printed holders,which stabilize the tissue surface within the focal plane of immersion objectives.Further computational image stabilization and noise reduction were applied,followed by superresolution radial fluctuations(SRRF)analysis,doubling image resolution,and enhancing signal-to-noise ratios for in vivo subcellular process investigation.Stabilization of<1μm was obtained by suction,and<25 nm were achieved by subsequent algorithmic image stabilization.A Mito-Dendra2 mouse model,expressing green fluorescent protein(GFP)in mitochondria,demonstrated the potential of long-term intravital subcellular imaging.In vivo mitochondrial fission and fusion,mitochondrial status migration,and the effects of alcohol consumption(modeled as an alcoholic liver disease)and berberine treatment on hepatocyte mitochondrial dynamics are directly observed intravitally.Suction-based stabilization in two-photon intravital imaging,coupled with computational super-resolution holds promise for advancing in vivo subcellular imaging studies.
基金sponsored by the National 973 Program(No.2011CB202402)the National Natural Science Foundation of China(No.41104069)the Fundamental Research Funds for the Central Universities(No.14CX06017A)
文摘The parabolic Radon transform has been widely used in multiple attenuation. To further improve the accuracy and efficiency of the Radon transform, we developed the 2- fdomain high-resolution Radon transform based on the fast and modified parabolic Radon transform presented by Abbad. The introduction of a new variable 2 makes the transform operator frequency-independent. Thus, we need to calculate the transform operator and its inverse operator only once, which greatly improves the computational efficiency. Besides, because the primaries and multiples are distributed on straight lines with different slopes in the 2-fdomain, we can easily choose the filtering operator to suppress the multiples. At the same time, the proposed method offers the advantage of high-resolution Radon transform, which can greatly improve the precision of attenuating the multiples. Numerical experiments suggest that the multiples are well suppressed and the amplitude versus offset characteristics of the primaries are well maintained. Real data processing results further verify the effectiveness and feasibility of the method.
基金financial support from the Civil Aviation Joint Funds of the National Natural Science Foundation of China (No’s.U1533203,61179069)
文摘Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional（4D） Trajectory-Based Operation（4DTBO）, which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CD＆R from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CD＆R scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism（STP） for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.
文摘For radar high resolution range profile (HRRP) recognition, three aspects are of great importance to improve the performance, i.e. discrimination for outlier, classification for inner and an accurate description for feature space. To tackle these issues, a novel target recognition method is designed, denoted by the multiple support vectors (multi-SV) method. With the proposed method, a special framework is constructed by a treble correlate support vector model to segment the feature space to two regions with the distribution of density, and then the description and classification hyperplane for each region are achieved. Based on the support vector framework, this method needs less memory and computation complexity to fit practical radar HRRP recognition. Finally, the experiment based on the measured data verifies the excellent performance of this method.
基金Sponsored by the National Natural Science Foundation of China (60232010 ,60572094)the National Science Foundation of China for Distin-guished Young Scholars (60625104)
文摘Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-component LFM signal were used by discrete fast fractional Fourier transform （FrFT）. Then the expression of chirp-rate resolution in fractional Fourier domain （FrFD） was deduced from discrete normalize time-frequency distribution, when multi-component LFM signal had only one center frequency. Furthermore, the detail influence of the sampling time, sampling frequency and chirp-rate upon the resolution was analyzed by partial differential equation. Simulation results and analysis indicate that increasing the sampling time can enhance the resolution, but the influence of the sampling frequency can he omitted. What＇s more, in multi-component LFM signal, the chirp-rate resolution of FrFT is no less than a minimal value, and it mainly dependent on the biggest value of chirp-rates, with which it has an approximately positive exponential relationship.
基金This research was a part of the projects titled"Development of Korea Operational Oceanographic System(KOOS),Phase2","Development of Environmental Information System for NSR Navigation","Base Research for Building Wide Integrated Surveillance System of Marine Territory",and"Construction of Ocean Research Stations and their Application Studies"funded by the Ministry of Oceans and Fisheries,Korea
文摘In the present article, we introduce a high resolution sea surface temperature （SST） product generated daily by Korea Institute of Ocean Science and Technology （KIOST）. The SST product is comprised of four sets of data including eight-hour and daily average SST data of I km resolution, and is based on the four infrared （IR） satellite SST data acquired by advanced very high resolution radiometer （AVHRR）, Moderate Resolution Imaging Spectroradiometer （MODIS）, Multifunctional Transport Satellites-2 （MTSAT-2） Imager and Meteorological Imager （MI）, two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2 （AMSR2）, and WindSAT with in-situ temperature data. These input satellite and in-situ SST data are merged by using the optimal interpolation （OI） algorithm. The root-mean-square-errors （RMSEs） of satellite and in-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from Ianuary to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71~C and the bias value was -0.08~C. The largest RMSE and bias were 0.86 and -0.26~C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Iapan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60~C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature （GHRSST） product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System （KOOS） as an input parameter for data assimilation.
基金supported by the National Natural Science Foundation of China (6087213461072117)
文摘Orthogonal frequency division multiplexing（OFDM） radar with multicarrier phase-coded waveforms has been recently introduced to achieve high range resolution.The conventional method for obtaining the high resolution range profile（HRRP） is based on matched filters.A method of synthesizing HRRP based on the fast Fourier transform（FFT） and decoding is proposed.The mathematical expressions of HRRP are derived by assuming an elementary scenario of point-scattering targets.Based on the characteristic of OFDM multicarrier signals,it mainly analyzes the influence on HRRP exerted by several factors,such as velocity compensation errors,the sampling frequency offset,and so on.The conclusions are significant for the design of the OFDM imaging radar.Finally,the simulation results demonstrate the validity of the conclusions.
基金supported by Safety Ability Project of Civil Aviation Administration of China(No.TM 2018-5-1/2)the Open Foundation project of The Graduate Student Innovation Base,China(Laboratory)of Nanjing University of Aeronautics and Astronautics,China(No.kfjj20190720)。
文摘With the rapid growth of flight flow,the workload of controllers is increasing daily,and handling flight conflicts is the main workload.Therefore,it is necessary to provide more efficient conflict resolution decision-making support for controllers.Due to the limitations of existing methods,they have not been widely used.In this paper,a Deep Reinforcement Learning(DRL)algorithm is proposed to resolve multi-aircraft flight conflict with high solving efficiency.First,the characteristics of multi-aircraft flight conflict problem are analyzed and the problem is modeled based on Markov decision process.Thus,the Independent Deep Q Network(IDQN)algorithm is used to solve the model.Simultaneously,a’downward-compatible’framework that supports dynamic expansion of the number of conflicting aircraft is designed.The model ultimately shows convergence through adequate training.Finally,the test conflict scenarios and indicators were used to verify the validity.In 700 scenarios,85.71%of conflicts were successfully resolved,and 71.51%of aircraft can reach destinations within 150 s around original arrival times.By contrast,conflict resolution algorithm based on DRL has great advantages in solution speed.The method proposed offers the possibility of decision-making support for controllers and reduce workload of controllers in future high-density airspace environment.
基金financial support by the Open Foundation of Chongqing Key Laboratory of Geomechanics and Geoenvironment Protection(Logistical Engineering University)(No.GKLGGP 2013-02)
文摘A multi-resolution rectangular shell element with membrane-bending based on the Kirchhoff-Love theory is proposed. The multi-resolution analysis （MRA） framework is formulated out of a mutually nesting displacement subspace sequence, whose basis functions are constructed of scaling and shifting on the element domain of basic node shape functions. The basic node shape functions are constructed from shifting to other three quadrants around a specific node of a basic element in one quadrant and joining the corresponding node shape functions of four elements at the specific node. The MRA endows the proposed element with the resolution level （RL） to adjust the element node number, thus modulating structural analysis accuracy accordingly. The node shape functions of Kronecker delta property make the treatment of element boundary condition quite convenient and enable the stiffness matrix and the loading column vectors of the proposed element to be automatically acquired through quadraturing around nodes in RL adjusting. As a result, the traditional 4-node rectangular shell element is a mono-resolution one and also a special case of the proposed element. The accuracy of a structural analysis is actually determined by the RL, not by the mesh. The simplicity and clarity of node shape function formulation with the Kronecker delta property, and the rational MRA enable the proposed element method to be implemented more rationally, easily and efficiently than the conventional mono-resolution rectangular shell element method or other corresponding MRA methods.
基金financial supports from National Natural Science Foundation of China(Grant Nos.U23A20368 and 62175006)Academic Excellence Foundation of BUAA for PhD Students.
文摘Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution sparse compound-eye camera(CEC)based on dual-end collaborative optimization is proposed,which provides a cost-effective way to break through the trade-off among the field of view,resolution,and imaging speed.In the optical end,a sparse CEC based on liquid lenses is designed,which can realize large-field-of-view imaging in real time,and fast zooming within 5 ms.In the computational end,a disturbed degradation model driven super-resolution network(DDMDSR-Net)is proposed to deal with complex image degradation issues in actual imaging situations,achieving high-robustness and high-fidelity resolution enhancement.Based on the proposed dual-end collaborative optimization framework,the angular resolution of the CEC can be enhanced from 71.6"to 26.0",which provides a solution to realize high-resolution imaging for array camera dispensing with high optical hardware complexity and data transmission bandwidth.Experiments verify the advantages of the CEC based on dual-end collaborative optimization in high-fidelity reconstruction of real scene images,kilometer-level long-distance detection,and dynamic imaging and precise recognition of targets of interest.
基金supported by the National Natural Science Foundation of China (No. 61773202)the National Key Laboratory of Air Traffic Control (No.SKLATM201706)the Sichuan Science and Technology Plan Project(No. 2018JZ0030).
文摘Based on ADS-B surveillance data,this paper proposes a multi-unmanned aerial vehicle(multi-UAV)collision detection method based on linear extrapolation for ground-based UAV collision detection and resolution,thus to provide early warning of possible conflicts.To address the problem of multi-UAV conflict,the basic ant colony algorithm is introduced.The conflict simplification model of the traditional basic ant colony algorithm is optimized by adding a speed regulation strategy.A multi-UAV conflict resolution scheme is presented based on speed regulation and heading strategies.The ant colony algorithm is improved by adding angle information and a queuing system.The results show that the improved ant colony algorithm can provide multi-UAV joint escape routes for a multi-UAV conflict situation in airspace.Unlike the traditional ant colony algorithm,our approach converges to the optimization target.The time required for the calculation is reduced by 43.9%,and the total delay distance caused by conflict resolution is reduced by 58.4%.
