Addressing the critical detection range limitation in active electrosensing(AES)for underwater sensing,this study proposes an enhanced AES system via novel array optimization.While AES offers advantages like interfere...Addressing the critical detection range limitation in active electrosensing(AES)for underwater sensing,this study proposes an enhanced AES system via novel array optimization.While AES offers advantages like interference immunity,acoustic stealth detection,and low cost,its short range restricts applicability.A target perturbation model under differential signal acquisition reveals that signal strength increases with local electric field intensity,target size,differential channel spacing,and conductivity contrast,but decreases with target-electrode distance.To extend detection,novel array configurations were explored.Simulations demonstrate that both rectangular and offset arrays significantly outperform the traditional collinear layout.Specifically,an offset array(with 8 m transmitting–receiving spacing)achieved an effective detection range enhancement exceeding 83%under the same distortion threshold while maintaining simplified electrode structure.Experimental validation confirmed a 100%increase in maximum detection distance to 5 m under identical noise thresholds compared to the collinear array.Furthermore,a fully connected neural network-based localization model achieved a mean positioning error of 14.12 cm at 3.15 m in static scenarios.In dynamic scenarios within 1–3 m,mean errors were controlled between 13.19 cm and 27.56 cm.Mechanistic analysis indicates that increasing the array baseline enhances the signal-to-noise ratio by simultaneously suppressing near-field environmental noise and amplifying far-field signal reception.Structural innovations in array design enabled this study to significantly expand the detection range of AES systems without compromising cost efficiency.These advancements directly promote the engineering application of AES technology,offering critical technical support for underwater defense security monitoring,long-range early warning systems,and maritime rights protection.展开更多
Accurate estimation of understory terrain has significant scientific importance for maintaining ecosystem balance and biodiversity conservation.Addressing the issue of inadequate representation of spatial heterogeneit...Accurate estimation of understory terrain has significant scientific importance for maintaining ecosystem balance and biodiversity conservation.Addressing the issue of inadequate representation of spatial heterogeneity when traditional forest topographic inversion methods consider the entire forest as the inversion unit,this study pro⁃poses a differentiated modeling approach to forest types based on refined land cover classification.Taking Puerto Ri⁃co and Maryland as study areas,a multi-dimensional feature system is constructed by integrating multi-source re⁃mote sensing data:ICESat-2 spaceborne LiDAR is used to obtain benchmark values for understory terrain,topo⁃graphic factors such as slope and aspect are extracted based on SRTM data,and vegetation cover characteristics are analyzed using Landsat-8 multispectral imagery.This study incorporates forest type as a classification modeling con⁃dition and applies the random forest algorithm to build differentiated topographic inversion models.Experimental re⁃sults indicate that,compared to traditional whole-area modeling methods(RMSE=5.06 m),forest type-based classi⁃fication modeling significantly improves the accuracy of understory terrain estimation(RMSE=2.94 m),validating the effectiveness of spatial heterogeneity modeling.Further sensitivity analysis reveals that canopy structure parame⁃ters(with RMSE variation reaching 4.11 m)exert a stronger regulatory effect on estimation accuracy compared to forest cover,providing important theoretical support for optimizing remote sensing models of forest topography.展开更多
This paper explores the recovery of block sparse signals in frame-based settings using the l_(2)/l_(q)-synthesis technique(0<q≤1).We propose a new null space property,referred to as block D-NSP_(q),which is based ...This paper explores the recovery of block sparse signals in frame-based settings using the l_(2)/l_(q)-synthesis technique(0<q≤1).We propose a new null space property,referred to as block D-NSP_(q),which is based on the dictionary D.We establish that matrices adhering to the block D-NSP_(q)condition are both necessary and sufficient for the exact recovery of block sparse signals via l_(2)/l_(q)-synthesis.Additionally,this condition is essential for the stable recovery of signals that are block-compressible with respect to D.This D-NSP_(q)property is identified as the first complete condition for successful signal recovery using l_(2)/l_(q)-synthesis.Furthermore,we assess the theoretical efficacy of the l2/lq-synthesis method under conditions of measurement noise.展开更多
A coordination polymer{[Cd(H_(2)dpa)(bpy)]·3H_(2)O}_(n)(Cd-CP)was designed and hydrothermal synthesized based on 4-(2,4-dicarboxyphenoxy)phthalic acid(H_(4)dpa),2,2'-bipyridine(bpy)and Cd(NO_(3))_(2)·4H_...A coordination polymer{[Cd(H_(2)dpa)(bpy)]·3H_(2)O}_(n)(Cd-CP)was designed and hydrothermal synthesized based on 4-(2,4-dicarboxyphenoxy)phthalic acid(H_(4)dpa),2,2'-bipyridine(bpy)and Cd(NO_(3))_(2)·4H_(2)O.The structure was characterized by single-crystal X-ray diffraction,powder X-ray diffraction,elemental analysis,and infrared spectroscopy.Cd-CP belongs to the monoclinic crystal system with the P2_1/c space group and performs in a 1D double-chain structure.The adjacent double chains further form a 3D supramolecular network structure through hydrogen bonding.Thermogravimetric analysis shows that Cd-CP has good thermal stability.Fluorescence analysis showed that Cd-CP had good choosing selectively and was sensitive to metal ions(Fe^(3+)and Zn^(2+)),2,4,6-trinitrophenylhydrazine(TRI),and pyrimethanil(Pth).Interestingly,when Cd-CP was used for fluorescence detection of metal ions,it was found to have a fluorescence quenching effect on Fe^(3+)but had an obvious enhancement effect on Zn^(2+).Therefore,we designed an“on-off-on”logic gate.In addition,the mechanism of fluorescence sensing has been deeply explored.CCDC:2258625.展开更多
Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investig...Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.展开更多
During the storage of composite propellants, the migration of plasticizers and other unbonded additives at the interfaces of liner adhesives has garnered significant attention in understanding liner failure mechanisms...During the storage of composite propellants, the migration of plasticizers and other unbonded additives at the interfaces of liner adhesives has garnered significant attention in understanding liner failure mechanisms, aging processes, and safety performance. However, there is currently no non-destructive and quantitative detection method for migration of plasticizers in propellant liner. In this study, we developed a HTPB sensing liner by incorporating conductive fillers-namely carbon black(CB), carbon nanotubes(CNTs), and graphene nanoplatelets(GNP)-into the HTPB matrix. The synergistic interaction between CNTs and GNP facilitates the formation of a tunneling conductive network that imparts electrical conductivity to the HTPB liner. To elucidate the functional relationship between conductivity and nitroglycerin(NG) migration, we applied the HTPB sensing liner onto double base propellant surfaces and measured both the conductivity of the sensing layer and NG migration during a 71°C accelerated aging experiment. The results shows that when CNTs/GNP content reaches 3wt%, there is an exponential correlation between conductivity and NG migration with a fitting degree of 0.9652;the average response sensitivity of ΔR/R0 relative to NG migration is calculated as 41.69, with an average deviation of merely5.67% between NG migrations derived from conductivity fittings compared to those obtained via TGA testing results. Overall, this sensing liner exhibits excellent capabilities for detecting NG migration nondestructively and quantitatively while offering a novel approach for assessing interfacial component migrations as well as debonding defects in propellants-a promising avenue for future self-monitoring strategies regarding propellant integrity.展开更多
In the field of satellite imagery, remote sensing image captioning(RSIC) is a hot topic with the challenge of overfitting and difficulty of image and text alignment. To address these issues, this paper proposes a visi...In the field of satellite imagery, remote sensing image captioning(RSIC) is a hot topic with the challenge of overfitting and difficulty of image and text alignment. To address these issues, this paper proposes a vision-language aligning paradigm for RSIC to jointly represent vision and language. First, a new RSIC dataset DIOR-Captions is built for augmenting object detection in optical remote(DIOR) sensing images dataset with manually annotated Chinese and English contents. Second, a Vision-Language aligning model with Cross-modal Attention(VLCA) is presented to generate accurate and abundant bilingual descriptions for remote sensing images. Third, a crossmodal learning network is introduced to address the problem of visual-lingual alignment. Notably, VLCA is also applied to end-toend Chinese captions generation by using the pre-training language model of Chinese. The experiments are carried out with various baselines to validate VLCA on the proposed dataset. The results demonstrate that the proposed algorithm is more descriptive and informative than existing algorithms in producing captions.展开更多
Compressed sensing(CS)is a novel technology to acquire and reconstruct sparse signals below the Nyquist rate.It has great potential in image and video acquisition and processing.To effectively improve the sparsity of ...Compressed sensing(CS)is a novel technology to acquire and reconstruct sparse signals below the Nyquist rate.It has great potential in image and video acquisition and processing.To effectively improve the sparsity of signal being measured and reconstructing efficiency,an encoding and decoding model of residual distributed compressive video sensing based on double side information(RDCVS-DSI)is proposed in this paper.Exploiting the characteristics of image itself in the frequency domain and the correlation between successive frames,the model regards the video frame in low quality as the first side information in the process of coding,and generates the second side information for the non-key frames using motion estimation and compensation technology at its decoding end.Performance analysis and simulation experiments show that the RDCVS-DSI model can rebuild the video sequence with high fidelity in the consumption of quite low complexity.About 1~5 dB gain in the average peak signal-to-noise ratio of the reconstructed frames is observed,and the speed is close to the least complex DCVS,when compared with prior works on compressive video sensing.展开更多
Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms us...Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms usually perform low accuracy.In this work,a sparsity adaptive signal reconstruction algorithm using sensing dictionary is proposed to achieve a lower reconstruction error.The sparsity estimation method is combined with the construction of the support set based on sensing dictionary.Using the adaptive sparsity method,an iterative signal reconstruction algorithm is proposed.The sufficient conditions for the exact signal reconstruction of the algorithm also is proved by theory.According to a series of simulations,the results show that the proposed method has higher precision compared with other state-of-the-art signal reconstruction algorithms especially in a high compression ratio scenarios.展开更多
The spontaneous burning has been lasting for thousands of years in the coal fields in the north of China. It spreads from the west (Tianshan coal field) to the east (Huolinhe coal field). Its E-W extension is up to 37...The spontaneous burning has been lasting for thousands of years in the coal fields in the north of China. It spreads from the west (Tianshan coal field) to the east (Huolinhe coal field). Its E-W extension is up to 3750km, concentrating in N35°toN45°, its vertical depth up to 260m, and the surface temprature locally up to 270℃. Annually, it burns out 0, 250-300 million tones of coal, causing economic loss equivalent to 2-3 billion R.M.B. Yuan.It destroies coal resources and causes hazards in coal mines. In order to locate the extent and the direction in coal burning areas, the remote sensing technique has heen used and has produced an obvious benefit.展开更多
A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conven...A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conventional CS-based methods where the joint spatial-temporal parameters are characterized in one large scale matrix,three smaller scale matrices with independent azimuth,elevation and Doppler frequency are introduced adopting a separable observation model.Afterwards,the estimation is achieved by L1-norm minimization and the Bayesian CS algorithm.In addition,under the L-shaped array topology,the azimuth and elevation are separated yet coupled to the same radial Doppler frequency.Hence,the pair matching problem is solved with the aid of the radial Doppler frequency.Finally,numerical simulations corroborate the feasibility and validity of the proposed algorithm.展开更多
LuF_(3):yb^(3+),Er^(3+)microcrystals codoped with Yb^(3+)(rtyb^(3+)/nLu3+=5%-15%)and Er^(3+)ions(nEJnLu3+=1%-5%)were synthesized by a facile hydrothermal process at different pH values.It is found that the pH value ha...LuF_(3):yb^(3+),Er^(3+)microcrystals codoped with Yb^(3+)(rtyb^(3+)/nLu3+=5%-15%)and Er^(3+)ions(nEJnLu3+=1%-5%)were synthesized by a facile hydrothermal process at different pH values.It is found that the pH value has a crucial effect on synthesis of the orthorhombic phase LuF_(3):yb^(3+),Er^(3+).Under 980 nm excitation,LuF_(3):yb^(3+),Ephosphors exhibit strong green upconversion(UC)emission bands centered at 523(2H11/12→4I.15.2)and 539 nm(4S3.2→4I15/3)and weak red emissions near 660 nm(4F9a→4I15/2).The optimum doping concentrations of Er^(3+)and Yb^(3+)for the highest emission intensity were determined by using X-ray diffraction(XRD)and photoluminescence(PL)analyses.Concentration dependent studies reveal that the optimal composition is 10%Yb^(3+)and 2%Er^(3+)co-doping concen-tration with a strong green emission.A possible UC mechanism for LuFg:yb^(3+),Er^(3+)depends on the pump power is discussed.The temperature dependence of the fluorescence intensity ratios(FIR)for the two green UC emission bands peaked at 523 and 539 nm was studied in the range of 293-573 K under excitation by a 980 nm diode laser and the maximum sensitivity was approximately 15.3×10^(-4)K^(-1)at 490 K.This indicates that LuF_(3):Yb^(3+),Er^(3+)phosphors are potential candidates for optical temperature sensors with high sensitivity.展开更多
The theory of compressed sensing （CS） provides a new chance to reduce the data acquisition time and improve the data usage factor of the stepped frequency radar system. In light of the sparsity of radar target refle...The theory of compressed sensing （CS） provides a new chance to reduce the data acquisition time and improve the data usage factor of the stepped frequency radar system. In light of the sparsity of radar target reflectivity, two imaging methods based on CS, termed the CS-based 2D joint imaging algorithm and the CS-based 2D decoupled imaging algorithm, are proposed. These methods incorporate the coherent mixing operation into the sparse dictionary, and take random measurements in both range and azimuth directions to get high resolution radar images, thus can remarkably reduce the data rate and simplify the hardware design of the radar system while maintaining imaging quality. Ex- periments from both simulated data and measured data in the anechoic chamber show that the proposed imaging methods can get more focused images than the traditional fast Fourier trans- form method. Wherein the joint algorithm has stronger robustness and can provide clearer inverse synthetic aperture radar images, while the decoupled algorithm is computationally more efficient but has slightly degraded imaging quality, which can be improved by increasing measurements or using a robuster recovery algorithm nevertheless.展开更多
How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classif...How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.展开更多
In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used...In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection(BP) and the data extraction method based on modified uniformly redundant arrays(MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing(CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally,by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.展开更多
An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption l...An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber laser.By combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric pollution.Extensive static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 km.Flight experiments is conducted with the helicopter.Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 s.The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety.展开更多
The development of image classification is one of the most important research topics in remote sensing. The prediction accuracy depends not only on the appropriate choice of the machine learning method but also on the...The development of image classification is one of the most important research topics in remote sensing. The prediction accuracy depends not only on the appropriate choice of the machine learning method but also on the quality of the training datasets. However, real-world data is not perfect and often suffers from noise. This paper gives an overview of noise filtering methods. Firstly, the types of noise and the consequences of class noise on machine learning are presented. Secondly, class noise handling methods at both the data level and the algorithm level are introduced. Then ensemble-based class noise handling methods including class noise removal, correction, and noise robust ensemble learners are presented. Finally, a summary of existing data-cleaning techniques is given.展开更多
Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple inpu...Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.展开更多
The zone of Yulong copper deposit is considered superlarge in scale all over the world, which is a part of Tethys to Himalaya Ore\|forming zone. The geological background of the Jinshajiang and Lancangjiang Faults pro...The zone of Yulong copper deposit is considered superlarge in scale all over the world, which is a part of Tethys to Himalaya Ore\|forming zone. The geological background of the Jinshajiang and Lancangjiang Faults provided utility for accumulated of copper, molybdenum and so on. The Yulong copper zone is the most important characteristic in the east Qinghai—Xizang Plateau (Tibet), which isabout 400km in length from north to south, and 30～70km in width from east to west. The structural channel for ores accumulation was constructed in Yanshan orogeny and the process of ore forming of the zone was mainly in Himalaya orogeny. The Yulong copper zone can be divided into three subzones, each named as north, south and east subzone which the north subzone is 50km in length of about NNW direction. Based on the geological interpretation (Fig.1), we understood that NW structures are distributed mainly in this area, then EW and NNW, and the sigmoid structures extended reflect their extrusion character. The EW and NNW structures are distributed in small scale and extended stable, which are cut to each other. The NNW structure was interpreted as undercover fracture, which may occurred earlier than NW one. Beside, of the structure, there are some differences in image tone, linear, relief, strata combination, structure pattern and so on. Therefore, the undercover fault played key efforts to Yulong copper formation.展开更多
基金supported in part by National Natural Science Foundation of China(Grant No.62273075).
文摘Addressing the critical detection range limitation in active electrosensing(AES)for underwater sensing,this study proposes an enhanced AES system via novel array optimization.While AES offers advantages like interference immunity,acoustic stealth detection,and low cost,its short range restricts applicability.A target perturbation model under differential signal acquisition reveals that signal strength increases with local electric field intensity,target size,differential channel spacing,and conductivity contrast,but decreases with target-electrode distance.To extend detection,novel array configurations were explored.Simulations demonstrate that both rectangular and offset arrays significantly outperform the traditional collinear layout.Specifically,an offset array(with 8 m transmitting–receiving spacing)achieved an effective detection range enhancement exceeding 83%under the same distortion threshold while maintaining simplified electrode structure.Experimental validation confirmed a 100%increase in maximum detection distance to 5 m under identical noise thresholds compared to the collinear array.Furthermore,a fully connected neural network-based localization model achieved a mean positioning error of 14.12 cm at 3.15 m in static scenarios.In dynamic scenarios within 1–3 m,mean errors were controlled between 13.19 cm and 27.56 cm.Mechanistic analysis indicates that increasing the array baseline enhances the signal-to-noise ratio by simultaneously suppressing near-field environmental noise and amplifying far-field signal reception.Structural innovations in array design enabled this study to significantly expand the detection range of AES systems without compromising cost efficiency.These advancements directly promote the engineering application of AES technology,offering critical technical support for underwater defense security monitoring,long-range early warning systems,and maritime rights protection.
基金Supported by the National Natural Science Foundation of China(42401488,42071351)the National Key Research and Development Program of China(2020YFA0608501,2017YFB0504204)+4 种基金the Liaoning Revitalization Talents Program(XLYC1802027)the Talent Recruited Program of the Chinese Academy of Science(Y938091)the Project Supported Discipline Innovation Team of the Liaoning Technical University(LNTU20TD-23)the Liaoning Province Doctoral Research Initiation Fund Program(2023-BS-202)the Basic Research Projects of Liaoning Department of Education(JYTQN2023202)。
文摘Accurate estimation of understory terrain has significant scientific importance for maintaining ecosystem balance and biodiversity conservation.Addressing the issue of inadequate representation of spatial heterogeneity when traditional forest topographic inversion methods consider the entire forest as the inversion unit,this study pro⁃poses a differentiated modeling approach to forest types based on refined land cover classification.Taking Puerto Ri⁃co and Maryland as study areas,a multi-dimensional feature system is constructed by integrating multi-source re⁃mote sensing data:ICESat-2 spaceborne LiDAR is used to obtain benchmark values for understory terrain,topo⁃graphic factors such as slope and aspect are extracted based on SRTM data,and vegetation cover characteristics are analyzed using Landsat-8 multispectral imagery.This study incorporates forest type as a classification modeling con⁃dition and applies the random forest algorithm to build differentiated topographic inversion models.Experimental re⁃sults indicate that,compared to traditional whole-area modeling methods(RMSE=5.06 m),forest type-based classi⁃fication modeling significantly improves the accuracy of understory terrain estimation(RMSE=2.94 m),validating the effectiveness of spatial heterogeneity modeling.Further sensitivity analysis reveals that canopy structure parame⁃ters(with RMSE variation reaching 4.11 m)exert a stronger regulatory effect on estimation accuracy compared to forest cover,providing important theoretical support for optimizing remote sensing models of forest topography.
基金Supported by The Featured Innovation Projects of the General University of Guangdong Province(2023KTSCX096)The Special Projects in Key Areas of Guangdong Province(ZDZX1088)Research Team Project of Guangdong University of Education(2024KYCXTD018)。
文摘This paper explores the recovery of block sparse signals in frame-based settings using the l_(2)/l_(q)-synthesis technique(0<q≤1).We propose a new null space property,referred to as block D-NSP_(q),which is based on the dictionary D.We establish that matrices adhering to the block D-NSP_(q)condition are both necessary and sufficient for the exact recovery of block sparse signals via l_(2)/l_(q)-synthesis.Additionally,this condition is essential for the stable recovery of signals that are block-compressible with respect to D.This D-NSP_(q)property is identified as the first complete condition for successful signal recovery using l_(2)/l_(q)-synthesis.Furthermore,we assess the theoretical efficacy of the l2/lq-synthesis method under conditions of measurement noise.
文摘A coordination polymer{[Cd(H_(2)dpa)(bpy)]·3H_(2)O}_(n)(Cd-CP)was designed and hydrothermal synthesized based on 4-(2,4-dicarboxyphenoxy)phthalic acid(H_(4)dpa),2,2'-bipyridine(bpy)and Cd(NO_(3))_(2)·4H_(2)O.The structure was characterized by single-crystal X-ray diffraction,powder X-ray diffraction,elemental analysis,and infrared spectroscopy.Cd-CP belongs to the monoclinic crystal system with the P2_1/c space group and performs in a 1D double-chain structure.The adjacent double chains further form a 3D supramolecular network structure through hydrogen bonding.Thermogravimetric analysis shows that Cd-CP has good thermal stability.Fluorescence analysis showed that Cd-CP had good choosing selectively and was sensitive to metal ions(Fe^(3+)and Zn^(2+)),2,4,6-trinitrophenylhydrazine(TRI),and pyrimethanil(Pth).Interestingly,when Cd-CP was used for fluorescence detection of metal ions,it was found to have a fluorescence quenching effect on Fe^(3+)but had an obvious enhancement effect on Zn^(2+).Therefore,we designed an“on-off-on”logic gate.In addition,the mechanism of fluorescence sensing has been deeply explored.CCDC:2258625.
文摘Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.
基金funded by Zhijian Laboratory Open Fund,Rocket Force University of Engineering(Grant No.2023-ZJSYS-KF01-03).
文摘During the storage of composite propellants, the migration of plasticizers and other unbonded additives at the interfaces of liner adhesives has garnered significant attention in understanding liner failure mechanisms, aging processes, and safety performance. However, there is currently no non-destructive and quantitative detection method for migration of plasticizers in propellant liner. In this study, we developed a HTPB sensing liner by incorporating conductive fillers-namely carbon black(CB), carbon nanotubes(CNTs), and graphene nanoplatelets(GNP)-into the HTPB matrix. The synergistic interaction between CNTs and GNP facilitates the formation of a tunneling conductive network that imparts electrical conductivity to the HTPB liner. To elucidate the functional relationship between conductivity and nitroglycerin(NG) migration, we applied the HTPB sensing liner onto double base propellant surfaces and measured both the conductivity of the sensing layer and NG migration during a 71°C accelerated aging experiment. The results shows that when CNTs/GNP content reaches 3wt%, there is an exponential correlation between conductivity and NG migration with a fitting degree of 0.9652;the average response sensitivity of ΔR/R0 relative to NG migration is calculated as 41.69, with an average deviation of merely5.67% between NG migrations derived from conductivity fittings compared to those obtained via TGA testing results. Overall, this sensing liner exhibits excellent capabilities for detecting NG migration nondestructively and quantitatively while offering a novel approach for assessing interfacial component migrations as well as debonding defects in propellants-a promising avenue for future self-monitoring strategies regarding propellant integrity.
基金supported by the National Natural Science Foundation of China (61702528,61806212)。
文摘In the field of satellite imagery, remote sensing image captioning(RSIC) is a hot topic with the challenge of overfitting and difficulty of image and text alignment. To address these issues, this paper proposes a vision-language aligning paradigm for RSIC to jointly represent vision and language. First, a new RSIC dataset DIOR-Captions is built for augmenting object detection in optical remote(DIOR) sensing images dataset with manually annotated Chinese and English contents. Second, a Vision-Language aligning model with Cross-modal Attention(VLCA) is presented to generate accurate and abundant bilingual descriptions for remote sensing images. Third, a crossmodal learning network is introduced to address the problem of visual-lingual alignment. Notably, VLCA is also applied to end-toend Chinese captions generation by using the pre-training language model of Chinese. The experiments are carried out with various baselines to validate VLCA on the proposed dataset. The results demonstrate that the proposed algorithm is more descriptive and informative than existing algorithms in producing captions.
基金Supported by National Natural Science Foundation of China(61170147)Major Cooperation Project of Production and College in Fujian Province(2012H61010016)Natural Science Foundation of Fujian Province(2013J01234)
文摘Compressed sensing(CS)is a novel technology to acquire and reconstruct sparse signals below the Nyquist rate.It has great potential in image and video acquisition and processing.To effectively improve the sparsity of signal being measured and reconstructing efficiency,an encoding and decoding model of residual distributed compressive video sensing based on double side information(RDCVS-DSI)is proposed in this paper.Exploiting the characteristics of image itself in the frequency domain and the correlation between successive frames,the model regards the video frame in low quality as the first side information in the process of coding,and generates the second side information for the non-key frames using motion estimation and compensation technology at its decoding end.Performance analysis and simulation experiments show that the RDCVS-DSI model can rebuild the video sequence with high fidelity in the consumption of quite low complexity.About 1~5 dB gain in the average peak signal-to-noise ratio of the reconstructed frames is observed,and the speed is close to the least complex DCVS,when compared with prior works on compressive video sensing.
基金supported by the National Natural Science Foundation of China(61773202,71874081)the Special Financial Grant from China Postdoctoral Science Foundation(2017T100366)+2 种基金the Key Laboratory of Avionics System Integrated Technology for National Defense Science and Technology,China Institute of Avionics Radio Electronics(6142505180407)the Open Fund of CAAC Key laboratory of General Aviation Operation,Civil Aviation Management Institute of China(CAMICKFJJ-2019-04)the Innovation Project of the Civil Aviation Administration of China(EAB19001)。
文摘Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms usually perform low accuracy.In this work,a sparsity adaptive signal reconstruction algorithm using sensing dictionary is proposed to achieve a lower reconstruction error.The sparsity estimation method is combined with the construction of the support set based on sensing dictionary.Using the adaptive sparsity method,an iterative signal reconstruction algorithm is proposed.The sufficient conditions for the exact signal reconstruction of the algorithm also is proved by theory.According to a series of simulations,the results show that the proposed method has higher precision compared with other state-of-the-art signal reconstruction algorithms especially in a high compression ratio scenarios.
文摘The spontaneous burning has been lasting for thousands of years in the coal fields in the north of China. It spreads from the west (Tianshan coal field) to the east (Huolinhe coal field). Its E-W extension is up to 3750km, concentrating in N35°toN45°, its vertical depth up to 260m, and the surface temprature locally up to 270℃. Annually, it burns out 0, 250-300 million tones of coal, causing economic loss equivalent to 2-3 billion R.M.B. Yuan.It destroies coal resources and causes hazards in coal mines. In order to locate the extent and the direction in coal burning areas, the remote sensing technique has heen used and has produced an obvious benefit.
文摘A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conventional CS-based methods where the joint spatial-temporal parameters are characterized in one large scale matrix,three smaller scale matrices with independent azimuth,elevation and Doppler frequency are introduced adopting a separable observation model.Afterwards,the estimation is achieved by L1-norm minimization and the Bayesian CS algorithm.In addition,under the L-shaped array topology,the azimuth and elevation are separated yet coupled to the same radial Doppler frequency.Hence,the pair matching problem is solved with the aid of the radial Doppler frequency.Finally,numerical simulations corroborate the feasibility and validity of the proposed algorithm.
文摘LuF_(3):yb^(3+),Er^(3+)microcrystals codoped with Yb^(3+)(rtyb^(3+)/nLu3+=5%-15%)and Er^(3+)ions(nEJnLu3+=1%-5%)were synthesized by a facile hydrothermal process at different pH values.It is found that the pH value has a crucial effect on synthesis of the orthorhombic phase LuF_(3):yb^(3+),Er^(3+).Under 980 nm excitation,LuF_(3):yb^(3+),Ephosphors exhibit strong green upconversion(UC)emission bands centered at 523(2H11/12→4I.15.2)and 539 nm(4S3.2→4I15/3)and weak red emissions near 660 nm(4F9a→4I15/2).The optimum doping concentrations of Er^(3+)and Yb^(3+)for the highest emission intensity were determined by using X-ray diffraction(XRD)and photoluminescence(PL)analyses.Concentration dependent studies reveal that the optimal composition is 10%Yb^(3+)and 2%Er^(3+)co-doping concen-tration with a strong green emission.A possible UC mechanism for LuFg:yb^(3+),Er^(3+)depends on the pump power is discussed.The temperature dependence of the fluorescence intensity ratios(FIR)for the two green UC emission bands peaked at 523 and 539 nm was studied in the range of 293-573 K under excitation by a 980 nm diode laser and the maximum sensitivity was approximately 15.3×10^(-4)K^(-1)at 490 K.This indicates that LuF_(3):Yb^(3+),Er^(3+)phosphors are potential candidates for optical temperature sensors with high sensitivity.
基金supported by the Prominent Youth Fund of the National Natural Science Foundation of China (61025006)
文摘The theory of compressed sensing （CS） provides a new chance to reduce the data acquisition time and improve the data usage factor of the stepped frequency radar system. In light of the sparsity of radar target reflectivity, two imaging methods based on CS, termed the CS-based 2D joint imaging algorithm and the CS-based 2D decoupled imaging algorithm, are proposed. These methods incorporate the coherent mixing operation into the sparse dictionary, and take random measurements in both range and azimuth directions to get high resolution radar images, thus can remarkably reduce the data rate and simplify the hardware design of the radar system while maintaining imaging quality. Ex- periments from both simulated data and measured data in the anechoic chamber show that the proposed imaging methods can get more focused images than the traditional fast Fourier trans- form method. Wherein the joint algorithm has stronger robustness and can provide clearer inverse synthetic aperture radar images, while the decoupled algorithm is computationally more efficient but has slightly degraded imaging quality, which can be improved by increasing measurements or using a robuster recovery algorithm nevertheless.
基金supported by the National Natural Science Foundation of China(U1435220)
文摘How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.
基金supported by the National Natural Science Foundation of China(6107116361071164+5 种基金6147119161501233)the Fundamental Research Funds for the Central Universities(NP2014504)the Aeronautical Science Foundation(20152052026)the Electronic & Information School of Yangtze University Innovation Foundation(2016-DXCX-05)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection(BP) and the data extraction method based on modified uniformly redundant arrays(MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing(CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally,by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.
文摘An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber laser.By combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric pollution.Extensive static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 km.Flight experiments is conducted with the helicopter.Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 s.The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety.
基金supported by the National Natural Science Foundation of China (62201438,61772397,12005169)the Basic Research Program of Natural Sciences of Shaanxi Province (2021JC-23)+2 种基金Yulin Science and Technology Bureau Science and Technology Development Special Project (CXY-2020-094)Shaanxi Forestry Science and Technology Innovation Key Project (SXLK2022-02-8)the Project of Shaanxi F ederation of Social Sciences (2022HZ1759)。
文摘The development of image classification is one of the most important research topics in remote sensing. The prediction accuracy depends not only on the appropriate choice of the machine learning method but also on the quality of the training datasets. However, real-world data is not perfect and often suffers from noise. This paper gives an overview of noise filtering methods. Firstly, the types of noise and the consequences of class noise on machine learning are presented. Secondly, class noise handling methods at both the data level and the algorithm level are introduced. Then ensemble-based class noise handling methods including class noise removal, correction, and noise robust ensemble learners are presented. Finally, a summary of existing data-cleaning techniques is given.
文摘Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.
文摘The zone of Yulong copper deposit is considered superlarge in scale all over the world, which is a part of Tethys to Himalaya Ore\|forming zone. The geological background of the Jinshajiang and Lancangjiang Faults provided utility for accumulated of copper, molybdenum and so on. The Yulong copper zone is the most important characteristic in the east Qinghai—Xizang Plateau (Tibet), which isabout 400km in length from north to south, and 30～70km in width from east to west. The structural channel for ores accumulation was constructed in Yanshan orogeny and the process of ore forming of the zone was mainly in Himalaya orogeny. The Yulong copper zone can be divided into three subzones, each named as north, south and east subzone which the north subzone is 50km in length of about NNW direction. Based on the geological interpretation (Fig.1), we understood that NW structures are distributed mainly in this area, then EW and NNW, and the sigmoid structures extended reflect their extrusion character. The EW and NNW structures are distributed in small scale and extended stable, which are cut to each other. The NNW structure was interpreted as undercover fracture, which may occurred earlier than NW one. Beside, of the structure, there are some differences in image tone, linear, relief, strata combination, structure pattern and so on. Therefore, the undercover fault played key efforts to Yulong copper formation.
