By multiplexing information symbols in the delay-Doppler(DD)domain,orthogonal time frequency space(OTFS)is a promising candidate for future wireless communication in high-mobility scenarios.In addition to the superior...By multiplexing information symbols in the delay-Doppler(DD)domain,orthogonal time frequency space(OTFS)is a promising candidate for future wireless communication in high-mobility scenarios.In addition to the superior communication performance,OTFS is also a natural choice for radar sensing since the primary parameters(range and velocity of targets)in radar signal processing can be inferred directly from the delay and Doppler shifts.Though there are several works on OTFS radar sensing,most of them consider the integer parameter estimation only,while the delay and Doppler shifts are usually fractional in the real world.In this paper,we propose a two-step method to estimate the fractional delay and Doppler shifts.We first perform the two-dimensional(2D)correlation between the received and transmitted DD domain symbols to obtain the integer parts of the parameters.Then a difference-based method is implemented to estimate the fractional parts of delay and Doppler indices.Meanwhile,we implement a target detection method based on a generalized likelihood ratio test since the number of potential targets in the sensing scenario is usually unknown.The simulation results show that the proposed method can obtain the delay and Doppler shifts accurately and get the number of sensing targets with a high detection probability.展开更多
Converged communication and radar sensing systems have attained increasing attention in recent years.The development of converged radar-data systems is reviewed,with a special focus on millimeter/terahertz systems as ...Converged communication and radar sensing systems have attained increasing attention in recent years.The development of converged radar-data systems is reviewed,with a special focus on millimeter/terahertz systems as a promising trend.Firstly,we present historical development and convergence technology concept for communication-radar systems,and highlight some emerging technologies in this area.We then provide an updated and comprehensive survey of several converged systems operating in different microwave and millimeter frequency bands,by providing some selective typical communication and radar sensing systems.In this part,we also summarize and compare the system performance in terms of maximum range/range resolution for radar mode and Bit Error Rate(BER)/wireless distance for communication mode.In the last section,the convergence of millimeter/terahertz communication-radar system is concluded by analyzing the prospect of millimeter-wave/terahertz technologies in providing ultrafast data rates and high resolution for our smart future.展开更多
Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to instal...Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to installation challenges and measurement artifacts that can compromise accuracy.This study presents a novel radar-based framework for non-contact motor imbalance detection using 24 GHz continuous-wave radar.A dataset of 1802 experimental trials was sourced,covering four imbalance levels(0,10,20,30 g)across varying motor speeds(500–1500 rpm)and load torques(0–3 Nm).Dual-channel in-phase and quadrature radar signals were captured at 10,000 samples per second for 30-s intervals,preserving both amplitude and phase information for analysis.A multi-domain feature extraction methodology captured imbalance signatures in time,frequency,and complex signal domains.From 65 initial features,statistical analysis using Kruskal–Wallis tests identified significant descriptors,and recursive feature elimination with Random Forest reduced the feature set to 20 dimensions,achieving 69%dimensionality reduction without loss of performance.Six machine learning algorithms,Random Forest,Extra Trees Classifier,Extreme Gradient Boosting,Categorical Boosting,Support Vector Machine with radial basis function kernel,and k-Nearest Neighbors were evaluated with grid-search hyperparameter optimization and five-fold cross-validation.The Extra Trees Classifier achieved the best performance with 98.52%test accuracy,98%cross-validation accuracy,and minimal variance,maintaining per-class precision and recall above 97%.Its superior performance is attributed to its randomized split selection and full bootstrapping strategy,which reduce variance and overfitting while effectively capturing the nonlinear feature interactions and non-normal distributions present in the dataset.The model’s average inference time of 70 ms enables near real-time deployment.Comparative analysis demonstrates that the radar-based framework matches or exceeds traditional contact-based methods while eliminating their inherent limitations,providing a robust,scalable,and noninvasive solution for industrial motor condition monitoring,particularly in hazardous or space-constrained environments.展开更多
The future of wireless systems is anticipated to revolutionize human connectivity through a diverse range of applications.The integration of multiple wireless functionalities into a unified system presents a critical ...The future of wireless systems is anticipated to revolutionize human connectivity through a diverse range of applications.The integration of multiple wireless functionalities into a unified system presents a critical challenge due to conflicting requirements in transceiver architecture and signal processing.Recent investigations are directing attention towards the development of systems that serve dual functions,like simultaneous wireless information and power transfer and radar-communication,aimed at boosting operational efficiency and ensuring seamless communication among different wireless capabilities.This review paper aims to discuss the architectural aspects of the integration of radar sensing,data communication,and power transfer.Firstly,the integration of radar sensing and data communication is studied for both cooperating and non-cooperating radar systems with conventional and interferometric architectures.Secondly,the power harvesting approach and internal energy recycling are discussed for the fusion of data communication and energy harvesting.Thirdly,radar sensing and power transfer integration is considered with special focus on harmonic backscattering and self-powered radars.Lastly,a roadmap for next-generation multifunction systems is outlined by considering several scenarios of multiplexing and architectures.展开更多
Radar remote sensing can acquire information of sub-surface covered by sand in arid area, detect surface roughness and vegetation coronet's layer and linear feature such as linear structure and channel sensitively...Radar remote sensing can acquire information of sub-surface covered by sand in arid area, detect surface roughness and vegetation coronet's layer and linear feature such as linear structure and channel sensitively. With sediment facies analysis, this paper studies the features of environmental evolution in mid-late Epipleistocene (60 ka BP-20 ka BP) in northeastern Ejin Banner. The conclusions are listed as follows: (1) The evolution of the three lakes, i.e. Gaxunnur, Sugunur and Tian'e lakes, are dominated by faults and regional climate. (2) By analyzing sedimentary section of old Juyanze Lake, the three lakes used to be a large outflow lake before 50 ka BP in northeastern Ejin Banner, and at 50 ka BP, temperature declined rapidly in northwestern China. The event caused the lake's shrinkage. (3) By fault activity uplift in the northern part of old Juyan Lake and depression in the southern part, the lake's water followed from north to south at around 35 ka BP, old Juyanze fluvial fan was formed. At the same time, Juyan Lake separated from Sugunur Lake and Wentugunr old channel was abandoned. (4) In recent 2000 years, Ruoshui River is a wandering river, sometimes it flows into Juyan Lake and sometimes Sugunur and Gaxunnur lakes. Due to human activities and over exploitation, the oasis ecosystem is rapidly degenerated in 15 years (1986-2000).展开更多
Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be co...Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.展开更多
Mangrove forests have important ecological functions in protecting the environment. However, the mangrove wetlands have been largely lost because of intensified human activities in the study area. Remote sensing can b...Mangrove forests have important ecological functions in protecting the environment. However, the mangrove wetlands have been largely lost because of intensified human activities in the study area. Remote sensing can be conveniently used for the inventory of mangrove forests because field investigation is very difficult. In this study, a knowledge-based system is developed to retrieve spatio-temporal dynamics of mangrove wetlands using multi-temporal remote sensing data. Radar remote sensing data are also used to provide complementary information for the quantitative analysis of mangrove wetlands. Radar remote sensing is able to penetrate mangrove forests and obtain the trunk information about mangrove structures. The integration of radar remote sensing with optical remote sensing can significantly improve the accuracies of classifying mangrove wetland types and estimating wetland biomass.展开更多
An imaging algorithm based on compressed sensing（CS） for the multi-ship motion target is presented. In order to reduce the quantity of data transmission in searching the ships on a large sea area, both range and azi...An imaging algorithm based on compressed sensing（CS） for the multi-ship motion target is presented. In order to reduce the quantity of data transmission in searching the ships on a large sea area, both range and azimuth of the moving ship targets are converted into sparse representation under certain signal basis. The signal reconstruction algorithm based on CS at a distant calculation station, and the Keystone and fractional Fourier transform（FRFT） algorithm are used to compensate range migration and obtain Doppler frequency. When the sea ships satisfy the sparsity, the algorithm can obtain higher resolution in both range and azimuth than the conventional imaging algorithm. Some simulations are performed to verify the reliability and stability.展开更多
As shallow salt lake resources are increasingly exploited,deep confined brine has become a strategic alternative due to its widespread distribution and significant reserve potential.However,unfavorable reservoir chara...As shallow salt lake resources are increasingly exploited,deep confined brine has become a strategic alternative due to its widespread distribution and significant reserve potential.However,unfavorable reservoir characteristics,particularly low permeability and poor recovery efficiency,have historically rendered these deposits uneconomic,restricting their utilization.Taking the Mahai Salt Lake in the Qaidam Basin as a representative case,this study investigates the structural controls on brine enrichment through an integrated approach.Previous long-term metallogenic studies and exploration data indicate occurrences of an extensional fault zone favorable for brine accumulation.Therefore,we applied InSAR deformation analysis to assess coseismic and postseismic surface responses.Combined with radon-222 emanation mapping,our findings reveal a strong spatial correlation between high-productivity brine boreholes and active fault systems.The existence of active faults enhance brine migration and storage,provided that the target reservoirs have substantial halite thickness and maintain relatively low clay-silt content.展开更多
The continuous development of smart agriculture puts forward the requirement of high accuracy slope path tracking for the agricultural wheel-legged robot.Compared to flat terrain,path tracking control on sloped terrai...The continuous development of smart agriculture puts forward the requirement of high accuracy slope path tracking for the agricultural wheel-legged robot.Compared to flat terrain,path tracking control on sloped terrain faces the obstacle of motion instability of the wheel-legged robot induced by the slope gravitational force component,which causes instantaneous steering center to offset.To address this problem,this study proposed a slope path tracking control algorithm by combining the methods of virtual sensing radar and two-level neural network.Firstly,the kinematic and dynamic models of the wheel-legged robot are deduced,from which the crucial factors affecting control accuracy of slope path tracking are recognized.Secondly,this study constructs the slope path tracking control algorithm,in which the virtual sensing radar is utilized to realize route perception,and the two-level neural network is employed to provide drive motors’speeds to adapt to path tracking on different slopes.Furthermore,the corresponding compensation methods of the identified impacting factors are embedded in the proposed algorithm,including the lateral tracking deviation factor,heading angle deviation factor,slope change factor,and slip rate factor.Finally,the co-simulation model of slope path tracking control is constructed,including the multi-body dynamic model of the wheel-legged robot in RecurDyn and the proposed slope path tracking algorithm complied by Python.Subsequently,the simulation tests of the wheel-legged robot are carried out under various slope angles and velocities.The results reveal that the proposed algorithm’s effectiveness and accuracy are superior,with tracking errors reduced by more than 47.2%compared to an optimized pure pursuit algorithm.展开更多
Soil moisture is a key parameter in the exchange of energy and water between the land surface and the atmosphere.This parameter plays an important role in the dynamics of permafrost on the Qinghai-Xizang Plateau,China...Soil moisture is a key parameter in the exchange of energy and water between the land surface and the atmosphere.This parameter plays an important role in the dynamics of permafrost on the Qinghai-Xizang Plateau,China,as well as in the related ecological and hydrological processes.However,the region's complex terrain and extreme climatic conditions result in low-accuracy soil moisture estimations using traditional remote sensing techniques.Thus,this study considered parameters of the backscatter coefficient of Sentinel-1A ground range detected(GRD)data,the polarization decomposition parameters of Sentinel-1A single-look complex(SLC)data,the normalized difference vegetation index(NDVI)based on Sentinel-2B data,and the topographic factors based on digital elevation model(DEM)data.By combining these parameters with a machine learning model,we established a feature selection rule.A cumulative importance threshold was derived for feature variables,and those variables that failed to meet the threshold were eliminated based on variations in the coefficient of determination(R^(2))and the unbiased root mean square error(ubRMSE).The eight most influential variables were selected and combined with the CatBoost model for soil moisture inversion,and the SHapley Additive exPlanations(SHAP)method was used to analyze the importance of these variables.The results demonstrated that the optimized model significantly improved the accuracy of soil moisture inversion.Compared to the unfiltered model,the optimal feature combination led to a 0.09 increase in R^(2)and a 0.7%reduction in ubRMSE.Ultimately,the optimized model achieved a R²of 0.87 and an ubRMSE of 5.6%.Analysis revealed that soil particle size had significant impact on soil water retention capacity.The impact of vegetation on the estimated soil moisture on the Qinghai-Xizang Plateau was considerable,demonstrating a significant positive correlation.Moreover,the microtopographical features of hummocks interfered with soil moisture estimation,indicating that such terrain effects warrant increased attention in future studies within the permafrost regions.The developed method not only enhances the accuracy of soil moisture retrieval in the complex terrain of the Qinghai-Xizang Plateau,but also exhibits high computational efficiency(with a relative time reduction of 18.5%),striking an excellent balance between accuracy and efficiency.This approach provides a robust framework for efficient soil moisture monitoring in remote areas with limited ground data,offering critical insights for ecological conservation,water resource management,and climate change adaptation on the Qinghai-Xizang Plateau.展开更多
It is very important to efficiently represent the target scattering characteristics in applications of polarimetric radar remote sensing. Three probability mass functions are introduced in this paper for target repres...It is very important to efficiently represent the target scattering characteristics in applications of polarimetric radar remote sensing. Three probability mass functions are introduced in this paper for target representation： using similarity parameters to describe target average scattering mechanism, using the eigenvalues of a target coherency matrix to describe target scattering randomness, and using radar received power to describe target scattering intensity. The concept of cross-entropy is employed to measure the difference between two scatterers based on the probability mass functions. Three parts of difference between scatterers are measured separately as the difference of average scattering mechanism, the difference of scattering randomness and the difference of scattering intensity, so that the usage of polarimetric data can be highly efficient and flexible. The supervised/unsupervised image classification schemes and their simplified versions are established based on the minimum cross-entropy principle. They are demonstrated to have better classification performance than the maximum likelihood classifier based on the Wishart distribution assumption, both in supervised and in unsupervised classification.展开更多
The development, state of art and prospects of application of the radar remote sensing technique are presented. The principle of the INSAR (Interferometric Synthetic Aperture Radar) technique is expounded in more de...The development, state of art and prospects of application of the radar remote sensing technique are presented. The principle of the INSAR (Interferometric Synthetic Aperture Radar) technique is expounded in more details. Some applications of this technique in measuring seismic dislocations are given. Finally, it is pointed out that INSAR has a non replaceable application potential in observing ground surface vertical deformations; it would provide an entirely new means and method for monitoring the dynamic field of earthquakes and give an extremely great impetus to the future earthquake prediction work.展开更多
This paper studies the development on the first order sea clutter cross section for bistatic high frequency surface wave radar (HFSWR). Based on the received first order electric field expression, a closed-form of cro...This paper studies the development on the first order sea clutter cross section for bistatic high frequency surface wave radar (HFSWR). Based on the received first order electric field expression, a closed-form of cross sections is derived to account for the case of receiving antenna array being mounted on the shipborne platform. The uniform linear motion and sway motion components are assumed to be responsible for the observed differences in comparison with the bistatic fixed antenna case. Correspondingly, simulations are conducted to study the sea clutter spectral characteristics for these two cases versus different system parameters and sea state conditions. It is shown numerically that the forward motion component will spread the Bragg lines severely and the influence triggered by the sway motion can be explained as the Bessel function modulation of the ordinary sea clutter spectra. The obtained results have important implications in the application of shipborne HFSWR technology to ocean remote sensing and target detection.展开更多
The integrated sensing and wireless power transfer(ISWPT)technology,in which the radar sensing and wireless power transfer functionalities are implemented using the same hardware platform,has been recently proposed.In...The integrated sensing and wireless power transfer(ISWPT)technology,in which the radar sensing and wireless power transfer functionalities are implemented using the same hardware platform,has been recently proposed.In this paper,we consider a near-field ISWPT system where one hybrid transmitter deploys extremely large-scale antenna arrays,and multiple energy receivers are located in the near-field region of the transmitter.Under such a new scenario,we study radar sensing and wireless power transfer performance trade-offs by optimizing the transmit beamforming vectors.In particular,we consider the transmit beampattern matching and max-min beampattern gain design metrics.For each radar performance metric,we aim to achieve the best performance of radar sensing,while guaranteeing the requirement of wireless power transfer.The corresponding beamforming design problems are non-convex,and the semi-definite relaxation(SDR)approach is applied to solve them globally optimally.Finally,numerical results verify the effectiveness of our proposed solutions.展开更多
Radio frequency(RF)signals have long been the invisible workhorses for the Internet of Things(IoT).They carry information through radio links,and perceive the world through radar sensing.A new idea now challenges us t...Radio frequency(RF)signals have long been the invisible workhorses for the Internet of Things(IoT).They carry information through radio links,and perceive the world through radar sensing.A new idea now challenges us to think differently:what if these RF waves could also compute?This is the central vision behind RF Computing.Here,RF signals act not only as carriers but as computational operands.展开更多
Flood incidents can massively damage and disrupt a city economic or governing core.However,flood risk can be mitigated through event planning and city-wide preparation to reduce damage.For,governments,firms,and civili...Flood incidents can massively damage and disrupt a city economic or governing core.However,flood risk can be mitigated through event planning and city-wide preparation to reduce damage.For,governments,firms,and civilians to make such preparations,flood susceptibility predictions are required.To predict flood susceptibility nine environmental related factors have been identified.They are elevation,slope,curvature,topographical wetness index(TWI),Euclidean distance from a river,land-cover,stream power index(SPI),soil type and precipitation.This work will use these environmental related factors alongside Sentinel-1 satellite imagery in a model intercomparison study to back-predict flood susceptibility in Jakarta for the January 2020 historic flood event across 260 key locations.For each location,this study uses current environmental conditions to predict flood status in the following month.Considering the imbalance between instances of flooded and non-flooded conditions,the Synthetic Minority Oversampling Technique(SMOTE)has been implemented to balance both classes in the training set.This work compares predictions from artificial neural networks(ANN),k-Nearest Neighbors algorithms(k-NN)and Support Vector Machines(SVM)against a random baseline.The effects of the SMOTE are also assessed by training each model on balanced and imbalanced datasets.The ANN is found to be superior to the other machine learning models.展开更多
文摘By multiplexing information symbols in the delay-Doppler(DD)domain,orthogonal time frequency space(OTFS)is a promising candidate for future wireless communication in high-mobility scenarios.In addition to the superior communication performance,OTFS is also a natural choice for radar sensing since the primary parameters(range and velocity of targets)in radar signal processing can be inferred directly from the delay and Doppler shifts.Though there are several works on OTFS radar sensing,most of them consider the integer parameter estimation only,while the delay and Doppler shifts are usually fractional in the real world.In this paper,we propose a two-step method to estimate the fractional delay and Doppler shifts.We first perform the two-dimensional(2D)correlation between the received and transmitted DD domain symbols to obtain the integer parts of the parameters.Then a difference-based method is implemented to estimate the fractional parts of delay and Doppler indices.Meanwhile,we implement a target detection method based on a generalized likelihood ratio test since the number of potential targets in the sensing scenario is usually unknown.The simulation results show that the proposed method can obtain the delay and Doppler shifts accurately and get the number of sensing targets with a high detection probability.
基金supported in part by National Natural Science Foundation of China(NSFC)under Grant No.61771424in part by Natural Science Foundation of Zhejiang Province under Grant No.LZ18F010001.
文摘Converged communication and radar sensing systems have attained increasing attention in recent years.The development of converged radar-data systems is reviewed,with a special focus on millimeter/terahertz systems as a promising trend.Firstly,we present historical development and convergence technology concept for communication-radar systems,and highlight some emerging technologies in this area.We then provide an updated and comprehensive survey of several converged systems operating in different microwave and millimeter frequency bands,by providing some selective typical communication and radar sensing systems.In this part,we also summarize and compare the system performance in terms of maximum range/range resolution for radar mode and Bit Error Rate(BER)/wireless distance for communication mode.In the last section,the convergence of millimeter/terahertz communication-radar system is concluded by analyzing the prospect of millimeter-wave/terahertz technologies in providing ultrafast data rates and high resolution for our smart future.
基金funded by Princess Nourah bint Abdulrahman University Researchers Support-ing Project number(PNURSP2026R346)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to installation challenges and measurement artifacts that can compromise accuracy.This study presents a novel radar-based framework for non-contact motor imbalance detection using 24 GHz continuous-wave radar.A dataset of 1802 experimental trials was sourced,covering four imbalance levels(0,10,20,30 g)across varying motor speeds(500–1500 rpm)and load torques(0–3 Nm).Dual-channel in-phase and quadrature radar signals were captured at 10,000 samples per second for 30-s intervals,preserving both amplitude and phase information for analysis.A multi-domain feature extraction methodology captured imbalance signatures in time,frequency,and complex signal domains.From 65 initial features,statistical analysis using Kruskal–Wallis tests identified significant descriptors,and recursive feature elimination with Random Forest reduced the feature set to 20 dimensions,achieving 69%dimensionality reduction without loss of performance.Six machine learning algorithms,Random Forest,Extra Trees Classifier,Extreme Gradient Boosting,Categorical Boosting,Support Vector Machine with radial basis function kernel,and k-Nearest Neighbors were evaluated with grid-search hyperparameter optimization and five-fold cross-validation.The Extra Trees Classifier achieved the best performance with 98.52%test accuracy,98%cross-validation accuracy,and minimal variance,maintaining per-class precision and recall above 97%.Its superior performance is attributed to its randomized split selection and full bootstrapping strategy,which reduce variance and overfitting while effectively capturing the nonlinear feature interactions and non-normal distributions present in the dataset.The model’s average inference time of 70 ms enables near real-time deployment.Comparative analysis demonstrates that the radar-based framework matches or exceeds traditional contact-based methods while eliminating their inherent limitations,providing a robust,scalable,and noninvasive solution for industrial motor condition monitoring,particularly in hazardous or space-constrained environments.
文摘The future of wireless systems is anticipated to revolutionize human connectivity through a diverse range of applications.The integration of multiple wireless functionalities into a unified system presents a critical challenge due to conflicting requirements in transceiver architecture and signal processing.Recent investigations are directing attention towards the development of systems that serve dual functions,like simultaneous wireless information and power transfer and radar-communication,aimed at boosting operational efficiency and ensuring seamless communication among different wireless capabilities.This review paper aims to discuss the architectural aspects of the integration of radar sensing,data communication,and power transfer.Firstly,the integration of radar sensing and data communication is studied for both cooperating and non-cooperating radar systems with conventional and interferometric architectures.Secondly,the power harvesting approach and internal energy recycling are discussed for the fusion of data communication and energy harvesting.Thirdly,radar sensing and power transfer integration is considered with special focus on harmonic backscattering and self-powered radars.Lastly,a roadmap for next-generation multifunction systems is outlined by considering several scenarios of multiplexing and architectures.
文摘Radar remote sensing can acquire information of sub-surface covered by sand in arid area, detect surface roughness and vegetation coronet's layer and linear feature such as linear structure and channel sensitively. With sediment facies analysis, this paper studies the features of environmental evolution in mid-late Epipleistocene (60 ka BP-20 ka BP) in northeastern Ejin Banner. The conclusions are listed as follows: (1) The evolution of the three lakes, i.e. Gaxunnur, Sugunur and Tian'e lakes, are dominated by faults and regional climate. (2) By analyzing sedimentary section of old Juyanze Lake, the three lakes used to be a large outflow lake before 50 ka BP in northeastern Ejin Banner, and at 50 ka BP, temperature declined rapidly in northwestern China. The event caused the lake's shrinkage. (3) By fault activity uplift in the northern part of old Juyan Lake and depression in the southern part, the lake's water followed from north to south at around 35 ka BP, old Juyanze fluvial fan was formed. At the same time, Juyan Lake separated from Sugunur Lake and Wentugunr old channel was abandoned. (4) In recent 2000 years, Ruoshui River is a wandering river, sometimes it flows into Juyan Lake and sometimes Sugunur and Gaxunnur lakes. Due to human activities and over exploitation, the oasis ecosystem is rapidly degenerated in 15 years (1986-2000).
基金supported by the National Natural Science Foundation of China(No.62171052 and No.61971054)the Fundamental Research Funds for the Central Universities(No.24820232023YQTD01).
文摘Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.
基金Natural Science Foundation of Guangdong, No.031647 ‘985 Project’ of GIS and Remote Sensing for Geosciences from the Ministry of Education of China
文摘Mangrove forests have important ecological functions in protecting the environment. However, the mangrove wetlands have been largely lost because of intensified human activities in the study area. Remote sensing can be conveniently used for the inventory of mangrove forests because field investigation is very difficult. In this study, a knowledge-based system is developed to retrieve spatio-temporal dynamics of mangrove wetlands using multi-temporal remote sensing data. Radar remote sensing data are also used to provide complementary information for the quantitative analysis of mangrove wetlands. Radar remote sensing is able to penetrate mangrove forests and obtain the trunk information about mangrove structures. The integration of radar remote sensing with optical remote sensing can significantly improve the accuracies of classifying mangrove wetland types and estimating wetland biomass.
基金supported by the National Natural Science Foundation of China(61271342)
文摘An imaging algorithm based on compressed sensing（CS） for the multi-ship motion target is presented. In order to reduce the quantity of data transmission in searching the ships on a large sea area, both range and azimuth of the moving ship targets are converted into sparse representation under certain signal basis. The signal reconstruction algorithm based on CS at a distant calculation station, and the Keystone and fractional Fourier transform（FRFT） algorithm are used to compensate range migration and obtain Doppler frequency. When the sea ships satisfy the sparsity, the algorithm can obtain higher resolution in both range and azimuth than the conventional imaging algorithm. Some simulations are performed to verify the reliability and stability.
基金supported by the National Key Research and Development Program Projects(2023YFC2906502 and 2018YFC0604801)。
文摘As shallow salt lake resources are increasingly exploited,deep confined brine has become a strategic alternative due to its widespread distribution and significant reserve potential.However,unfavorable reservoir characteristics,particularly low permeability and poor recovery efficiency,have historically rendered these deposits uneconomic,restricting their utilization.Taking the Mahai Salt Lake in the Qaidam Basin as a representative case,this study investigates the structural controls on brine enrichment through an integrated approach.Previous long-term metallogenic studies and exploration data indicate occurrences of an extensional fault zone favorable for brine accumulation.Therefore,we applied InSAR deformation analysis to assess coseismic and postseismic surface responses.Combined with radon-222 emanation mapping,our findings reveal a strong spatial correlation between high-productivity brine boreholes and active fault systems.The existence of active faults enhance brine migration and storage,provided that the target reservoirs have substantial halite thickness and maintain relatively low clay-silt content.
基金supported by the National Key R&D Program of China(Grant No.2022YFD2202102)the Key Laboratory of Modern Agricultural Intelligent Equipment in South China,Ministry of Agriculture and Rural Affairs,China.
文摘The continuous development of smart agriculture puts forward the requirement of high accuracy slope path tracking for the agricultural wheel-legged robot.Compared to flat terrain,path tracking control on sloped terrain faces the obstacle of motion instability of the wheel-legged robot induced by the slope gravitational force component,which causes instantaneous steering center to offset.To address this problem,this study proposed a slope path tracking control algorithm by combining the methods of virtual sensing radar and two-level neural network.Firstly,the kinematic and dynamic models of the wheel-legged robot are deduced,from which the crucial factors affecting control accuracy of slope path tracking are recognized.Secondly,this study constructs the slope path tracking control algorithm,in which the virtual sensing radar is utilized to realize route perception,and the two-level neural network is employed to provide drive motors’speeds to adapt to path tracking on different slopes.Furthermore,the corresponding compensation methods of the identified impacting factors are embedded in the proposed algorithm,including the lateral tracking deviation factor,heading angle deviation factor,slope change factor,and slip rate factor.Finally,the co-simulation model of slope path tracking control is constructed,including the multi-body dynamic model of the wheel-legged robot in RecurDyn and the proposed slope path tracking algorithm complied by Python.Subsequently,the simulation tests of the wheel-legged robot are carried out under various slope angles and velocities.The results reveal that the proposed algorithm’s effectiveness and accuracy are superior,with tracking errors reduced by more than 47.2%compared to an optimized pure pursuit algorithm.
基金supported by the Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology(13230550)the Coal Industry Engineering Research Center of Mining Area Environmental and Disaster Cooperative Monitoring,Anhui University of Science and Technology(KSXTJC202305)+1 种基金the State Key Laboratory of Geodesy and Earth's Dynamics,Innovation Academy for Precision Measurement Science and Technology(SKLGED2023-5-1)the China Postdoctoral Science Foundation(2023M733604).
文摘Soil moisture is a key parameter in the exchange of energy and water between the land surface and the atmosphere.This parameter plays an important role in the dynamics of permafrost on the Qinghai-Xizang Plateau,China,as well as in the related ecological and hydrological processes.However,the region's complex terrain and extreme climatic conditions result in low-accuracy soil moisture estimations using traditional remote sensing techniques.Thus,this study considered parameters of the backscatter coefficient of Sentinel-1A ground range detected(GRD)data,the polarization decomposition parameters of Sentinel-1A single-look complex(SLC)data,the normalized difference vegetation index(NDVI)based on Sentinel-2B data,and the topographic factors based on digital elevation model(DEM)data.By combining these parameters with a machine learning model,we established a feature selection rule.A cumulative importance threshold was derived for feature variables,and those variables that failed to meet the threshold were eliminated based on variations in the coefficient of determination(R^(2))and the unbiased root mean square error(ubRMSE).The eight most influential variables were selected and combined with the CatBoost model for soil moisture inversion,and the SHapley Additive exPlanations(SHAP)method was used to analyze the importance of these variables.The results demonstrated that the optimized model significantly improved the accuracy of soil moisture inversion.Compared to the unfiltered model,the optimal feature combination led to a 0.09 increase in R^(2)and a 0.7%reduction in ubRMSE.Ultimately,the optimized model achieved a R²of 0.87 and an ubRMSE of 5.6%.Analysis revealed that soil particle size had significant impact on soil water retention capacity.The impact of vegetation on the estimated soil moisture on the Qinghai-Xizang Plateau was considerable,demonstrating a significant positive correlation.Moreover,the microtopographical features of hummocks interfered with soil moisture estimation,indicating that such terrain effects warrant increased attention in future studies within the permafrost regions.The developed method not only enhances the accuracy of soil moisture retrieval in the complex terrain of the Qinghai-Xizang Plateau,but also exhibits high computational efficiency(with a relative time reduction of 18.5%),striking an excellent balance between accuracy and efficiency.This approach provides a robust framework for efficient soil moisture monitoring in remote areas with limited ground data,offering critical insights for ecological conservation,water resource management,and climate change adaptation on the Qinghai-Xizang Plateau.
基金This work was supported in part by the National Natural Science Foundation of China(Grant No．40271077)the National Important Fundamental Research Plan of China(Grant No．2001CB309401)+3 种基金the Science Foundation of National Defence of Chinathe Research Fund for the Doctoral Program of Higher Education of Chinathe Aerospace Technology Foundation of Chinaand the Fundam ental Research Foundation of Tsinghua University．
文摘It is very important to efficiently represent the target scattering characteristics in applications of polarimetric radar remote sensing. Three probability mass functions are introduced in this paper for target representation： using similarity parameters to describe target average scattering mechanism, using the eigenvalues of a target coherency matrix to describe target scattering randomness, and using radar received power to describe target scattering intensity. The concept of cross-entropy is employed to measure the difference between two scatterers based on the probability mass functions. Three parts of difference between scatterers are measured separately as the difference of average scattering mechanism, the difference of scattering randomness and the difference of scattering intensity, so that the usage of polarimetric data can be highly efficient and flexible. The supervised/unsupervised image classification schemes and their simplified versions are established based on the minimum cross-entropy principle. They are demonstrated to have better classification performance than the maximum likelihood classifier based on the Wishart distribution assumption, both in supervised and in unsupervised classification.
文摘The development, state of art and prospects of application of the radar remote sensing technique are presented. The principle of the INSAR (Interferometric Synthetic Aperture Radar) technique is expounded in more details. Some applications of this technique in measuring seismic dislocations are given. Finally, it is pointed out that INSAR has a non replaceable application potential in observing ground surface vertical deformations; it would provide an entirely new means and method for monitoring the dynamic field of earthquakes and give an extremely great impetus to the future earthquake prediction work.
基金supported by the National Natural Science Foundation of China(61471144)
文摘This paper studies the development on the first order sea clutter cross section for bistatic high frequency surface wave radar (HFSWR). Based on the received first order electric field expression, a closed-form of cross sections is derived to account for the case of receiving antenna array being mounted on the shipborne platform. The uniform linear motion and sway motion components are assumed to be responsible for the observed differences in comparison with the bistatic fixed antenna case. Correspondingly, simulations are conducted to study the sea clutter spectral characteristics for these two cases versus different system parameters and sea state conditions. It is shown numerically that the forward motion component will spread the Bragg lines severely and the influence triggered by the sway motion can be explained as the Bessel function modulation of the ordinary sea clutter spectra. The obtained results have important implications in the application of shipborne HFSWR technology to ocean remote sensing and target detection.
基金supported by the National Natural Science Foundation of China(No.61971238).
文摘The integrated sensing and wireless power transfer(ISWPT)technology,in which the radar sensing and wireless power transfer functionalities are implemented using the same hardware platform,has been recently proposed.In this paper,we consider a near-field ISWPT system where one hybrid transmitter deploys extremely large-scale antenna arrays,and multiple energy receivers are located in the near-field region of the transmitter.Under such a new scenario,we study radar sensing and wireless power transfer performance trade-offs by optimizing the transmit beamforming vectors.In particular,we consider the transmit beampattern matching and max-min beampattern gain design metrics.For each radar performance metric,we aim to achieve the best performance of radar sensing,while guaranteeing the requirement of wireless power transfer.The corresponding beamforming design problems are non-convex,and the semi-definite relaxation(SDR)approach is applied to solve them globally optimally.Finally,numerical results verify the effectiveness of our proposed solutions.
文摘Radio frequency(RF)signals have long been the invisible workhorses for the Internet of Things(IoT).They carry information through radio links,and perceive the world through radar sensing.A new idea now challenges us to think differently:what if these RF waves could also compute?This is the central vision behind RF Computing.Here,RF signals act not only as carriers but as computational operands.
文摘Flood incidents can massively damage and disrupt a city economic or governing core.However,flood risk can be mitigated through event planning and city-wide preparation to reduce damage.For,governments,firms,and civilians to make such preparations,flood susceptibility predictions are required.To predict flood susceptibility nine environmental related factors have been identified.They are elevation,slope,curvature,topographical wetness index(TWI),Euclidean distance from a river,land-cover,stream power index(SPI),soil type and precipitation.This work will use these environmental related factors alongside Sentinel-1 satellite imagery in a model intercomparison study to back-predict flood susceptibility in Jakarta for the January 2020 historic flood event across 260 key locations.For each location,this study uses current environmental conditions to predict flood status in the following month.Considering the imbalance between instances of flooded and non-flooded conditions,the Synthetic Minority Oversampling Technique(SMOTE)has been implemented to balance both classes in the training set.This work compares predictions from artificial neural networks(ANN),k-Nearest Neighbors algorithms(k-NN)and Support Vector Machines(SVM)against a random baseline.The effects of the SMOTE are also assessed by training each model on balanced and imbalanced datasets.The ANN is found to be superior to the other machine learning models.
