Dual-Doppler radar detection and wind-field retrieval techniques are crucial for capturing small-scale structures within convective systems.The spatiotemporal resolution of radar data is a key factor influencing the a...Dual-Doppler radar detection and wind-field retrieval techniques are crucial for capturing small-scale structures within convective systems.The spatiotemporal resolution of radar data is a key factor influencing the accuracy of wind-field observations.Recently,an advanced X-band phased-array weather radar system was deployed in Foshan,Guangdong Province,China,comprising a central collaborative control unit and multiple networked phased-array radar front-ends.These radar front-ends work together to scan a common area,achieving a maximum data time difference of 5 s and a volume scan interval of 30 s,thereby providing three-dimensional wind-field data with higher spatiotemporal resolution and greater accuracy than achieved using traditional methods.This study utilized the X-band phased-array weather radar system to analyze the development of a substantial hailstorm that occurred over Foshan on 26 March 2022.Analysis indicated that hail cloud activity intensified considerably after 1442 local time,with the maximum reflectivity factor exceeding 60 dBZ above the altitude of the-20℃ level,and reflectivity continued to increase over the subsequent 12 min.More precise information on the flow-field structure of the storm was obtained by examining the X-band radar data.The temporal and vertical variations in the maximum reflectivity factor,updraft velocity,vertical wind shear,and horizontal wind speed within a hailstorm cloud were scrutinized.The results show that the altitude,intensity,and range of the main updraft area increased as the storm core ascended.Concurrently,the vertical wind shear at mid-lower levels of the storm became more pronounced as the altitude of the strong radar echo center increased prior to the peak of the updraft.Therefore,a new hail warning index was developed by using the vertical wind shear,and the index can be used to issue warnings up to 12 min earlier than achievable using traditional methods detecting increases in hailstorm intensity.展开更多
A novel adaptive sampling interval algorithm for multitarget tracking is presented. This algorithm which is based on interacting multiple models incorporates the grey relational grade （GRG） into the particle swarm o...A novel adaptive sampling interval algorithm for multitarget tracking is presented. This algorithm which is based on interacting multiple models incorporates the grey relational grade （GRG） into the particle swarm optimization （PSO）. Firstly, the desired tracking accuracy is set for each target. Secondly, sampling intervals are selected as particles, and then the advantage of the GRG is taken as the measurement function for resource management. Meanwhile, the fitness value of the PSO is used to measure the difference between desired tracking accuracy and estimated tracking accuracy. Finally, it is suggested that the radar should track the target whose prediction value of the next sampling interval is the smallest. Simulations show that the proposed method improves both the tracking accuracy and tracking efficiency of the phased-array radar.展开更多
An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability ...An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane,a mobile X-band Doppler radar （XDR） and XPAR were installed at the same site to observe convective precipitation events.Nearby S-band operational radar （SA） data were also collected to examine the reflectivity bias of XPAR.An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented.The reflectivity and velocity biases of XPAR are examined with SA and XDR.Reflectivity sensitivities,the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed.The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation,and the averaged reflectivity differences between XPAR and XDR,and XDR and SA,were 0.4 dB and 6.6 dB on 13 July and-4.5 dB and 5.1 dB on 2 August 2012,respectively.The minimum observed reflectivities at a range of 50 km for XPAR,XDR and SA were about 15.4 dBZ,13.5 dBZ and-3.5 dBZ,respectively.The bias of velocity between XPAR and XDR was negligible.This study provides a possible method for the quantitative comparison of the XPAR data,as well as the sensitivity of reflectivity,calibration,gain and bias introduced by pulse compression.展开更多
The strong destructive winds during tornadoes can greatly threaten human life and destroy property.The increasing availability of visual and remote observations,especially by Doppler weather radars,is of great value i...The strong destructive winds during tornadoes can greatly threaten human life and destroy property.The increasing availability of visual and remote observations,especially by Doppler weather radars,is of great value in understanding tornado formation and issuing warnings to the public.In this study,we present the first documented tornado over water detected by a state-of-the-art dual-polarization phased-array radar(dual-PAR)in China.In contrast to new-generation weather radars,the dual-PAR shows great advantages in tornado detection for its high spatial resolution,reliable polarimetric variables,and rapid-scan strategy.The polarimetric signature of copolar cross-correlation coefficient with anomalously low magnitude appears to be effective for verifying a tornado and thus is helpful for issuing tornado warnings.The Guangdong Meteorological Service has been developing an experimental X-band dual-PAR network in the Pearl River Delta with the goal of deploying at least 40 advanced dual-PARs and other dual-polarization weather radars before 2035.This network is the first quasi-operational X-band dual-PAR network with unprecedented high coverage in the globe.With such high-performance close-range PARs,efficient operational nowcasting and warning services for small-scale,rapidly evolving,and damaging weather(e.g.,tornadoes,localized heavy rainfall,microbursts,and hail)can be expected.展开更多
The performance of different quantitative precipitation estimation(QPE) relationships is examined using the polarimetric variables from the X-band polarimetric phased-array radars in Guangzhou,China.Three QPE approach...The performance of different quantitative precipitation estimation(QPE) relationships is examined using the polarimetric variables from the X-band polarimetric phased-array radars in Guangzhou,China.Three QPE approaches,namely,R(ZH),R(ZH,ZDR) and R(KDP),are developed for horizontal reflectivity,differential reflectivity and specific phase shift rate,respectively.The estimation parameters are determined by fitting the relationships to the observed radar variables using the T-matrix method.The QPE relationships were examined using the data of four heavy precipitation events in southern China.The examination shows that the R(ZH) approach performs better for the precipitation rate less than 5 mm h-1, and R(KDP) is better for the rate higher than 5 mm h-1, while R(ZH,ZDR) has the worst performance.An adaptive approach is developed by taking the advantages of both R(ZH) and R(KDP) approaches to improve the QPE accuracy.展开更多
The meteor radar can detect the zenith angle,azimuth,radial velocity,and altitude of meteor trails so that one can invert the wind profiles in the mesosphere and low thermosphere(MLT)region,based on the Interferometri...The meteor radar can detect the zenith angle,azimuth,radial velocity,and altitude of meteor trails so that one can invert the wind profiles in the mesosphere and low thermosphere(MLT)region,based on the Interferometric and Doppler techniques.In this paper,the horizontal wind field,gravity wave(GW)disturbance variance,and GW fluxes are analyzed through the meteor radar observation from 2012−2022,at Mohe(53.5°N,122.4°E)and Zuoling(30.5°N,114.6°E)stations of the(Chinese)Meridian Project.The Lomb−Scargle periodogram method has been utilized to analyze the periodic variations for time series with observational data gaps.The results show that the zonal winds at both stations are eastward dominated,while the meridional winds are southward dominated.The variance of GW disturbances in the zonal and meridional directions increases gradually with height,and there is a strong pattern of annual variation.The zonal momentum flux of GW changes little with height,showing weak annual variation.The meridional GW flux varies gradually from northward to southward with height,and the annual periodicity is stronger.For both stations,the maximum values of zonal and meridional wind occur close to the peak heights of GW flux,with opposite directions.This observational evidence is consistent with the filtering theory.The horizontal wind velocity,GW flux,and disturbance variance of the GW at Mohe are overall smaller than those at Zuoling,indicating weaker activities in the MLT at Mohe.The power spectral density(PSD)calculated by the Lomb−Scargle periodogram shows that there are 12-month period and 6-month period in horizontal wind field,GW disturbance variance and GW flux at both stations,and especially there is also a 4-month cycle in the disturbance variance.The PSD of the 12-month and 6-month cycles exhibits maximum values below 88 km and above 94 km.展开更多
Accurate knowledge of mesospheric winds and waves is essential for studying the dynamics and climate in the mesosphere and lower thermosphere(MLT)region.In this study,we conduct a comparative analysis of the mesospher...Accurate knowledge of mesospheric winds and waves is essential for studying the dynamics and climate in the mesosphere and lower thermosphere(MLT)region.In this study,we conduct a comparative analysis of the mesosphere tidal results obtained from two adjacent meteor radars at low latitudes in Kunming,China,from November 2013 to December 2014.These two radars operate at different frequencies of 37.5 MHz and 53.1 MHz,respectively.However,overall good agreement is observed between the two radars in terms of horizontal winds and tide observations.The results show that the dominant tidal waves of the zonal and meridional winds are diurnal and semidiurnal tides.Moreover,we conduct an exhaustive statistical analysis to compare the tidal amplitudes and vertical wavelengths recorded by the dual radar systems,which reveals a high degree of alignment in tidal dynamics.The investigation includes variances and covariances of tidal amplitudes,which demonstrate remarkable consistency across measurements from both radars.This finding highlights clear uniformity in the mesospheric tidal patterns observed at low latitudes by the two neighboring meteor radars.Results of the comparative analysis specifically underscore the significant correlation in vertical wavelength measurements,validating the robustness of radar observations for tidal research.展开更多
Cognitive bias,stemming from electronic measurement error and variability in human perception,exists in cognitive electronic warfare and affects the outcomes of conflicts.In this paper,the dynamic game approach is emp...Cognitive bias,stemming from electronic measurement error and variability in human perception,exists in cognitive electronic warfare and affects the outcomes of conflicts.In this paper,the dynamic game approach is employed to develop a model for cognitive bias induced by incomplete information and measurement errors in cognitive radar countermeasures.The payoffs for both parties are calculated using the radar's anti-jamming strategy matrix A and the jammer's jamming strategy matrix B.With perfect Bayesian equilibrium,a dynamic radar countermeasure model is established,and the impact of cognitive bias is analyzed.Drawing inspiration from the cognitive bias analysis method used in stock market trading,a cognitive bias model for cognitive radar countermeasures is introduced,and its correctness is mathematically proved.A gaming scenario involving the AN/SPY-1 radar and a smart jammer is set up to analyze the influence of cognitive bias on game outcomes.Simulation results validate the effectiveness of the proposed method.展开更多
This paper addresses the design problem of an embedded mobile stage location system based on a two-dimensional laser radar.The mobile stage is a piece of important performance equipment in art performances,and the pos...This paper addresses the design problem of an embedded mobile stage location system based on a two-dimensional laser radar.The mobile stage is a piece of important performance equipment in art performances,and the positioning problem is one of the key issues in the control of the mobile stage.Both hardware and software are developed for the mobile stage.The hardware of the location system consists of a laser radar,an embedded control board,a wireless router,and a motion control unit.The software of the location system includes embedded software and human-machine interface(HMI),and they are designed to achieve the functions of real-time positioning and monitoring.First,a novel landmark identification method is presented based on the landmark reflection intensities and shapes.Then,the initial pose of the mobile stage is calculated by using the triangle matching algorithm and the least squares method.A distributed fusion Kalman filtering algorithm is applied to fuse landmark information and odometer information to achieve real-time positioning of the mobile stage.The designed system has been implemented in a practical mobile stage,and the results demonstrate that the location system can achieve a high positioning precision in both the stationary and moving scenarios.展开更多
High Andean ecosystems within microbasins serve as crucial areas for water recharge,containing both surface and subsurface moisture.However,these ecosystems are currently under threat due to overgrazing,degradation,an...High Andean ecosystems within microbasins serve as crucial areas for water recharge,containing both surface and subsurface moisture.However,these ecosystems are currently under threat due to overgrazing,degradation,and the impacts of climate change.The objective is to validate the subsoil moisture of bofedal estimated using ground-penetrating radar(GPR)data in comparison to in-situ measurements obtained with a soil moisture meter(SMM)in the Apacheta microbasin of the Ayacucho region.The validation method involves comparing soil moisture values obtained with the SMM,with the estimated dielectric permittivity(DP)values from GPR surveys along four transects(T)in a bofedal.Reflected wave amplitude data are converted to DP values to identify water pockets(70<DP<81)and saturated soil moisture(10<DP<40).An analysis of the determination coefficient R^(2)and the Kappa index(κ)was conducted between both groups of bofedal subsoil moisture data along the four surveyed transects at depths ranging from 0 to 24 cm that contain water and saturated moisture.T1 contains a volume of 1,16 m^(3)(47.85%),T2 has 0.98 m^(3)(46.6%),T3 lacks water(40.8%),and T4 holds 0.63 m^(3)(31.45%).The correlation of DP data with SMM for T1(R^(2)=0.801),T2(R^(2)=0.949),T3(R^(2)=0:837)y T4(R^(2)=0.842)implies that the SMM measurements significantly explain the estimated DP.Moreover,the kappa test demonstrated good agreement reliability between both observations made with GPR and SMM,with κ=0.763;[95%CI:0.471-1.055],indicating that the GPR method for measuring subsoil moisture is acceptable with an 87.5%confidence level.展开更多
Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering systems.However, research on PHM framework development for rad...Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering systems.However, research on PHM framework development for radar systems is limited. Furthermore, typical PHM approaches are centralized, do not scale well, and are challenging to implement.This paper proposes an integrated PHM framework for radar systems based on system structural decomposition to enhance reliability and support maintenance actions. The complexity challenge associated with implementing PHM at the system level is addressed by dividing the radar system into subsystems. Subsequently, optimal measurement point selection and sensor placement algorithms are formulated for effective data acquisition. Local modules are developed for each subsystem health assessment, fault diagnosis, and fault prediction without a centralized controller. Maintenance decisions are based on each local module’s fault diagnosis and prediction results. To further improve the effectiveness of the prognostics stage, the feasibility of integrating deep learning (DL) models is also investigated.Several experiments with different degradation patterns are performed to evaluate the effectiveness of the framework’s DLbased prognostics model. The proposed framework facilitates transitioning from traditional reactive maintenance practices to a predictive maintenance approach, thereby reducing downtime and improving the overall availability of radar systems.展开更多
To resolve the data combination of Phased-array Ground Penetrating Radar (PAGPR), we first build a model of PAGPR and a layered model, and then a new data combination algorithm is presented based on it. This method ca...To resolve the data combination of Phased-array Ground Penetrating Radar (PAGPR), we first build a model of PAGPR and a layered model, and then a new data combination algorithm is presented based on it. This method calculates time delay of multi-receivers, basing on the signal of the nearest receiver, then shifts other signals and adds them up, and gets one signal at last. It has been proved that this method can restrain noise, multiple waves, clutter waves and improve the precision of time location. In the end, an example is given to prove the method's efficiency.展开更多
According to the frequency property of Phasedarray ground penetrating radar (PGPR), this paper gives a frequency point slice method based on Wigner time-frequency analysis. This method solves the problem of analysis f...According to the frequency property of Phasedarray ground penetrating radar (PGPR), this paper gives a frequency point slice method based on Wigner time-frequency analysis. This method solves the problem of analysis for the PGPR's superposition data and makes detecting outcome simpler and detecting target more recognizable. At last, the analytical results of road test data of the Three Gorges prove the analytical method efficient. Key words phased-array ground penetrating radar - wigner time-frequency analysis - superposition data - object identification CLC number TN 715.7 Foundation item: Supported by the National Nature Science Foundation of China (50099620) and 863 Program Foundation of China (2001AA132050-03)Biography: ZOU Lian (1975-), male, Ph. D candidate, research direction: signal processing.展开更多
A novel weather radar system with distributed phased-array front-ends was developed. The specifications and preliminary data synthesis of this system are presented, which comprises one back-end and three or more front...A novel weather radar system with distributed phased-array front-ends was developed. The specifications and preliminary data synthesis of this system are presented, which comprises one back-end and three or more front-ends. Each front-end, which utilizes a phased-array digital beamforming technology, sequentially transmits four 22.5°-width beams to cover the 0°–90° elevational scan within about 0.05 s. The azimuthal detection is completed by one mechanical scan of0°–360° azimuths within about 12 s volume-scan update time. In the case of three front-ends, they are deployed according to an acute triangle to form a fine detection area(FDA). Because of the triangular deployment of multiple phased-array front-ends and a unique synchronized azimuthal scanning(SAS) rule, this new radar system is named Array Weather Radar(AWR). The back-end controls the front-ends to scan strictly in accordance with the SAS rule that assures the data time differences(DTD) among the three front-ends are less than 2 s for the same detection point in the FDA. The SAS can maintain DTD < 2 s for an expanded seven-front-end AWR. With the smallest DTD, gridded wind fields are derived from AWR data, by sampling of the interpolated grid, onto a rectangular grid of 100 m ×100 m ×100 m at a 12 s temporal resolution in the FDA. The first X-band single-polarized three-front-end AWR was deployed in field experiments in 2018 at Huanghua International Airport, China. Having completed the data synthesis and processing, the preliminary observation results of the first AWR are described herein.展开更多
Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target...Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target parameters and target direction estimation is difficult in radar MLJ.A target parameter estimation method via atom-reconstruction in radar MLJ is proposed in this paper.The proposed method can suppress the MLJ and simultaneously provide high estimation accuracy of target range and angle.Precisely,the eigen-projection matrix processing(EMP)algorithm is adopted to suppress the MLJ,and the target range is estimated effectively through the beamforming and pulse compression.Then the target angle can be effectively estimated by the atom-reconstruction method.Without any prior knowledge,the MLJ can be canceled,and the angle estimation accuracy is well preserved.Furthermore,the proposed method does not have strict requirement for radar array construction,and it can be applied for linear array and planar array.Moreover,the proposed method can effectively estimate the target azimuth and elevation simultaneously when the target azimuth(or elevation)equals to the jamming azimuth(or elevation),because the MLJ is suppressed in spatial plane dimension.展开更多
Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic h...Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.展开更多
In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance...In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.展开更多
Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a mult...Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.展开更多
In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes consid...In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is followed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.展开更多
The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology...The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.展开更多
基金Supported by the Joint Fund Project of National Natural Science Foundation of China(U2142210).
文摘Dual-Doppler radar detection and wind-field retrieval techniques are crucial for capturing small-scale structures within convective systems.The spatiotemporal resolution of radar data is a key factor influencing the accuracy of wind-field observations.Recently,an advanced X-band phased-array weather radar system was deployed in Foshan,Guangdong Province,China,comprising a central collaborative control unit and multiple networked phased-array radar front-ends.These radar front-ends work together to scan a common area,achieving a maximum data time difference of 5 s and a volume scan interval of 30 s,thereby providing three-dimensional wind-field data with higher spatiotemporal resolution and greater accuracy than achieved using traditional methods.This study utilized the X-band phased-array weather radar system to analyze the development of a substantial hailstorm that occurred over Foshan on 26 March 2022.Analysis indicated that hail cloud activity intensified considerably after 1442 local time,with the maximum reflectivity factor exceeding 60 dBZ above the altitude of the-20℃ level,and reflectivity continued to increase over the subsequent 12 min.More precise information on the flow-field structure of the storm was obtained by examining the X-band radar data.The temporal and vertical variations in the maximum reflectivity factor,updraft velocity,vertical wind shear,and horizontal wind speed within a hailstorm cloud were scrutinized.The results show that the altitude,intensity,and range of the main updraft area increased as the storm core ascended.Concurrently,the vertical wind shear at mid-lower levels of the storm became more pronounced as the altitude of the strong radar echo center increased prior to the peak of the updraft.Therefore,a new hail warning index was developed by using the vertical wind shear,and the index can be used to issue warnings up to 12 min earlier than achievable using traditional methods detecting increases in hailstorm intensity.
基金supported by the Pre-research Fund (N0901-041)the Funding of Jiangsu Innovation Program for Graduate Education(CX09B 081Z CX10B 110Z)
文摘A novel adaptive sampling interval algorithm for multitarget tracking is presented. This algorithm which is based on interacting multiple models incorporates the grey relational grade （GRG） into the particle swarm optimization （PSO）. Firstly, the desired tracking accuracy is set for each target. Secondly, sampling intervals are selected as particles, and then the advantage of the GRG is taken as the measurement function for resource management. Meanwhile, the fitness value of the PSO is used to measure the difference between desired tracking accuracy and estimated tracking accuracy. Finally, it is suggested that the radar should track the target whose prediction value of the next sampling interval is the smallest. Simulations show that the proposed method improves both the tracking accuracy and tracking efficiency of the phased-array radar.
基金funded by National High-Tech Research and Development Projects (863 Grant No. 2007AA061901)+2 种基金the National Key Program for Developing Basic Sciences (Grant No. 2012CB417202)the National Natural Science Foundation of China (Grant No. 41175038)the Public Welfare Meteorological Special Project (Grant No. GYHY201106046)
文摘An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane,a mobile X-band Doppler radar （XDR） and XPAR were installed at the same site to observe convective precipitation events.Nearby S-band operational radar （SA） data were also collected to examine the reflectivity bias of XPAR.An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented.The reflectivity and velocity biases of XPAR are examined with SA and XDR.Reflectivity sensitivities,the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed.The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation,and the averaged reflectivity differences between XPAR and XDR,and XDR and SA,were 0.4 dB and 6.6 dB on 13 July and-4.5 dB and 5.1 dB on 2 August 2012,respectively.The minimum observed reflectivities at a range of 50 km for XPAR,XDR and SA were about 15.4 dBZ,13.5 dBZ and-3.5 dBZ,respectively.The bias of velocity between XPAR and XDR was negligible.This study provides a possible method for the quantitative comparison of the XPAR data,as well as the sensitivity of reflectivity,calibration,gain and bias introduced by pulse compression.
基金Key-Area R&D Program of Guangdong Province(2020B1111200001)National Key R&D Program of China(2017YFC1501701)+1 种基金National Natural Science Foundation of China(41875051)Guangzhou Municipal Science and Technology Planning Project(201903010101)
文摘The strong destructive winds during tornadoes can greatly threaten human life and destroy property.The increasing availability of visual and remote observations,especially by Doppler weather radars,is of great value in understanding tornado formation and issuing warnings to the public.In this study,we present the first documented tornado over water detected by a state-of-the-art dual-polarization phased-array radar(dual-PAR)in China.In contrast to new-generation weather radars,the dual-PAR shows great advantages in tornado detection for its high spatial resolution,reliable polarimetric variables,and rapid-scan strategy.The polarimetric signature of copolar cross-correlation coefficient with anomalously low magnitude appears to be effective for verifying a tornado and thus is helpful for issuing tornado warnings.The Guangdong Meteorological Service has been developing an experimental X-band dual-PAR network in the Pearl River Delta with the goal of deploying at least 40 advanced dual-PARs and other dual-polarization weather radars before 2035.This network is the first quasi-operational X-band dual-PAR network with unprecedented high coverage in the globe.With such high-performance close-range PARs,efficient operational nowcasting and warning services for small-scale,rapidly evolving,and damaging weather(e.g.,tornadoes,localized heavy rainfall,microbursts,and hail)can be expected.
基金Guangzhou Science and Technology Plan Project(202103000030)Guangdong Meteorological Bureau Science and Technology Project(GRMC2020Z08)a project co-funded by the Development Team of Radar Application and Severe Convection Early Warning Technology(GRMCTD202002)。
文摘The performance of different quantitative precipitation estimation(QPE) relationships is examined using the polarimetric variables from the X-band polarimetric phased-array radars in Guangzhou,China.Three QPE approaches,namely,R(ZH),R(ZH,ZDR) and R(KDP),are developed for horizontal reflectivity,differential reflectivity and specific phase shift rate,respectively.The estimation parameters are determined by fitting the relationships to the observed radar variables using the T-matrix method.The QPE relationships were examined using the data of four heavy precipitation events in southern China.The examination shows that the R(ZH) approach performs better for the precipitation rate less than 5 mm h-1, and R(KDP) is better for the rate higher than 5 mm h-1, while R(ZH,ZDR) has the worst performance.An adaptive approach is developed by taking the advantages of both R(ZH) and R(KDP) approaches to improve the QPE accuracy.
基金supported by the Fundamental Research Funds for the Central Universities,CHD(NO.300102263205 and NO.300102264916)the West Light Cross-Disciplinary Innovation team of Chinese Academy of Sciences(NO.E1294301).supported by the Fundamental Research Funds for the Central Universities,CHD(NO.300102263205 and NO.300102264916)the West Light Cross-Disciplinary Innovation team of Chinese Academy of Sciences(NO.E1294301).
文摘The meteor radar can detect the zenith angle,azimuth,radial velocity,and altitude of meteor trails so that one can invert the wind profiles in the mesosphere and low thermosphere(MLT)region,based on the Interferometric and Doppler techniques.In this paper,the horizontal wind field,gravity wave(GW)disturbance variance,and GW fluxes are analyzed through the meteor radar observation from 2012−2022,at Mohe(53.5°N,122.4°E)and Zuoling(30.5°N,114.6°E)stations of the(Chinese)Meridian Project.The Lomb−Scargle periodogram method has been utilized to analyze the periodic variations for time series with observational data gaps.The results show that the zonal winds at both stations are eastward dominated,while the meridional winds are southward dominated.The variance of GW disturbances in the zonal and meridional directions increases gradually with height,and there is a strong pattern of annual variation.The zonal momentum flux of GW changes little with height,showing weak annual variation.The meridional GW flux varies gradually from northward to southward with height,and the annual periodicity is stronger.For both stations,the maximum values of zonal and meridional wind occur close to the peak heights of GW flux,with opposite directions.This observational evidence is consistent with the filtering theory.The horizontal wind velocity,GW flux,and disturbance variance of the GW at Mohe are overall smaller than those at Zuoling,indicating weaker activities in the MLT at Mohe.The power spectral density(PSD)calculated by the Lomb−Scargle periodogram shows that there are 12-month period and 6-month period in horizontal wind field,GW disturbance variance and GW flux at both stations,and especially there is also a 4-month cycle in the disturbance variance.The PSD of the 12-month and 6-month cycles exhibits maximum values below 88 km and above 94 km.
基金supported by the National Natural Science Foundation of China (Grant Nos. 42125402 and 42174183)the National Key Technologies R&D Program of China (Grant No.2022YFF0503703)+2 种基金the B-type Strategic Priority Program of the Chinese Academy of Sciences (Grant No. XDB41000000)the foundation of the National Key Laboratory of Electromagnetic Environment and the Fundamental Research Funds for the Central Universitiesthe Chinese Meridian Project
文摘Accurate knowledge of mesospheric winds and waves is essential for studying the dynamics and climate in the mesosphere and lower thermosphere(MLT)region.In this study,we conduct a comparative analysis of the mesosphere tidal results obtained from two adjacent meteor radars at low latitudes in Kunming,China,from November 2013 to December 2014.These two radars operate at different frequencies of 37.5 MHz and 53.1 MHz,respectively.However,overall good agreement is observed between the two radars in terms of horizontal winds and tide observations.The results show that the dominant tidal waves of the zonal and meridional winds are diurnal and semidiurnal tides.Moreover,we conduct an exhaustive statistical analysis to compare the tidal amplitudes and vertical wavelengths recorded by the dual radar systems,which reveals a high degree of alignment in tidal dynamics.The investigation includes variances and covariances of tidal amplitudes,which demonstrate remarkable consistency across measurements from both radars.This finding highlights clear uniformity in the mesospheric tidal patterns observed at low latitudes by the two neighboring meteor radars.Results of the comparative analysis specifically underscore the significant correlation in vertical wavelength measurements,validating the robustness of radar observations for tidal research.
文摘Cognitive bias,stemming from electronic measurement error and variability in human perception,exists in cognitive electronic warfare and affects the outcomes of conflicts.In this paper,the dynamic game approach is employed to develop a model for cognitive bias induced by incomplete information and measurement errors in cognitive radar countermeasures.The payoffs for both parties are calculated using the radar's anti-jamming strategy matrix A and the jammer's jamming strategy matrix B.With perfect Bayesian equilibrium,a dynamic radar countermeasure model is established,and the impact of cognitive bias is analyzed.Drawing inspiration from the cognitive bias analysis method used in stock market trading,a cognitive bias model for cognitive radar countermeasures is introduced,and its correctness is mathematically proved.A gaming scenario involving the AN/SPY-1 radar and a smart jammer is set up to analyze the influence of cognitive bias on game outcomes.Simulation results validate the effectiveness of the proposed method.
基金Supported by the Philosophy and Social Sciences Planning Project of Zhejiang Province(No.23NDJC374YB)the Major Humanities and Social Sciences Research Projects in Zhejiang Higher Education Institutions(No.2024QN067).
文摘This paper addresses the design problem of an embedded mobile stage location system based on a two-dimensional laser radar.The mobile stage is a piece of important performance equipment in art performances,and the positioning problem is one of the key issues in the control of the mobile stage.Both hardware and software are developed for the mobile stage.The hardware of the location system consists of a laser radar,an embedded control board,a wireless router,and a motion control unit.The software of the location system includes embedded software and human-machine interface(HMI),and they are designed to achieve the functions of real-time positioning and monitoring.First,a novel landmark identification method is presented based on the landmark reflection intensities and shapes.Then,the initial pose of the mobile stage is calculated by using the triangle matching algorithm and the least squares method.A distributed fusion Kalman filtering algorithm is applied to fuse landmark information and odometer information to achieve real-time positioning of the mobile stage.The designed system has been implemented in a practical mobile stage,and the results demonstrate that the location system can achieve a high positioning precision in both the stationary and moving scenarios.
基金funded by Institute for Research and Innovation of the National University of San Cristobal de Huamanga-UNSCH.
文摘High Andean ecosystems within microbasins serve as crucial areas for water recharge,containing both surface and subsurface moisture.However,these ecosystems are currently under threat due to overgrazing,degradation,and the impacts of climate change.The objective is to validate the subsoil moisture of bofedal estimated using ground-penetrating radar(GPR)data in comparison to in-situ measurements obtained with a soil moisture meter(SMM)in the Apacheta microbasin of the Ayacucho region.The validation method involves comparing soil moisture values obtained with the SMM,with the estimated dielectric permittivity(DP)values from GPR surveys along four transects(T)in a bofedal.Reflected wave amplitude data are converted to DP values to identify water pockets(70<DP<81)and saturated soil moisture(10<DP<40).An analysis of the determination coefficient R^(2)and the Kappa index(κ)was conducted between both groups of bofedal subsoil moisture data along the four surveyed transects at depths ranging from 0 to 24 cm that contain water and saturated moisture.T1 contains a volume of 1,16 m^(3)(47.85%),T2 has 0.98 m^(3)(46.6%),T3 lacks water(40.8%),and T4 holds 0.63 m^(3)(31.45%).The correlation of DP data with SMM for T1(R^(2)=0.801),T2(R^(2)=0.949),T3(R^(2)=0:837)y T4(R^(2)=0.842)implies that the SMM measurements significantly explain the estimated DP.Moreover,the kappa test demonstrated good agreement reliability between both observations made with GPR and SMM,with κ=0.763;[95%CI:0.471-1.055],indicating that the GPR method for measuring subsoil moisture is acceptable with an 87.5%confidence level.
基金National Natural Science Foundation of China (42027805)。
文摘Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering systems.However, research on PHM framework development for radar systems is limited. Furthermore, typical PHM approaches are centralized, do not scale well, and are challenging to implement.This paper proposes an integrated PHM framework for radar systems based on system structural decomposition to enhance reliability and support maintenance actions. The complexity challenge associated with implementing PHM at the system level is addressed by dividing the radar system into subsystems. Subsequently, optimal measurement point selection and sensor placement algorithms are formulated for effective data acquisition. Local modules are developed for each subsystem health assessment, fault diagnosis, and fault prediction without a centralized controller. Maintenance decisions are based on each local module’s fault diagnosis and prediction results. To further improve the effectiveness of the prognostics stage, the feasibility of integrating deep learning (DL) models is also investigated.Several experiments with different degradation patterns are performed to evaluate the effectiveness of the framework’s DLbased prognostics model. The proposed framework facilitates transitioning from traditional reactive maintenance practices to a predictive maintenance approach, thereby reducing downtime and improving the overall availability of radar systems.
文摘To resolve the data combination of Phased-array Ground Penetrating Radar (PAGPR), we first build a model of PAGPR and a layered model, and then a new data combination algorithm is presented based on it. This method calculates time delay of multi-receivers, basing on the signal of the nearest receiver, then shifts other signals and adds them up, and gets one signal at last. It has been proved that this method can restrain noise, multiple waves, clutter waves and improve the precision of time location. In the end, an example is given to prove the method's efficiency.
文摘According to the frequency property of Phasedarray ground penetrating radar (PGPR), this paper gives a frequency point slice method based on Wigner time-frequency analysis. This method solves the problem of analysis for the PGPR's superposition data and makes detecting outcome simpler and detecting target more recognizable. At last, the analytical results of road test data of the Three Gorges prove the analytical method efficient. Key words phased-array ground penetrating radar - wigner time-frequency analysis - superposition data - object identification CLC number TN 715.7 Foundation item: Supported by the National Nature Science Foundation of China (50099620) and 863 Program Foundation of China (2001AA132050-03)Biography: ZOU Lian (1975-), male, Ph. D candidate, research direction: signal processing.
基金supported by Natural Science Foundation of China(NSFC)(Grant No.31727901)。
文摘A novel weather radar system with distributed phased-array front-ends was developed. The specifications and preliminary data synthesis of this system are presented, which comprises one back-end and three or more front-ends. Each front-end, which utilizes a phased-array digital beamforming technology, sequentially transmits four 22.5°-width beams to cover the 0°–90° elevational scan within about 0.05 s. The azimuthal detection is completed by one mechanical scan of0°–360° azimuths within about 12 s volume-scan update time. In the case of three front-ends, they are deployed according to an acute triangle to form a fine detection area(FDA). Because of the triangular deployment of multiple phased-array front-ends and a unique synchronized azimuthal scanning(SAS) rule, this new radar system is named Array Weather Radar(AWR). The back-end controls the front-ends to scan strictly in accordance with the SAS rule that assures the data time differences(DTD) among the three front-ends are less than 2 s for the same detection point in the FDA. The SAS can maintain DTD < 2 s for an expanded seven-front-end AWR. With the smallest DTD, gridded wind fields are derived from AWR data, by sampling of the interpolated grid, onto a rectangular grid of 100 m ×100 m ×100 m at a 12 s temporal resolution in the FDA. The first X-band single-polarized three-front-end AWR was deployed in field experiments in 2018 at Huanghua International Airport, China. Having completed the data synthesis and processing, the preliminary observation results of the first AWR are described herein.
基金supported by the National Natural Science Foundation of China(6207148262001510)the Civil Aviation Administration o f China(U1733116)。
文摘Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target parameters and target direction estimation is difficult in radar MLJ.A target parameter estimation method via atom-reconstruction in radar MLJ is proposed in this paper.The proposed method can suppress the MLJ and simultaneously provide high estimation accuracy of target range and angle.Precisely,the eigen-projection matrix processing(EMP)algorithm is adopted to suppress the MLJ,and the target range is estimated effectively through the beamforming and pulse compression.Then the target angle can be effectively estimated by the atom-reconstruction method.Without any prior knowledge,the MLJ can be canceled,and the angle estimation accuracy is well preserved.Furthermore,the proposed method does not have strict requirement for radar array construction,and it can be applied for linear array and planar array.Moreover,the proposed method can effectively estimate the target azimuth and elevation simultaneously when the target azimuth(or elevation)equals to the jamming azimuth(or elevation),because the MLJ is suppressed in spatial plane dimension.
基金the National Natural Science Foundation of China(22265021)the Aeronautical Science Foundation of China(2020Z056056003).
文摘Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.
基金supported by the National Natural Science Foundation of China(62171447)。
文摘In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.
基金supported by National Key R&D Program of China(Grant No.2022YFC3003903)the S&T Program of Hebei(Grant No.19275408D),the Key-Area Research and Development Program of Guangdong Province(Grant No.2020B1111200001)+1 种基金the Key Project of Monitoring,Early Warning and Prevention of Major Natural Disasters of China(Grant No.2019YFC1510304)the Joint Fund of Key Laboratory of Atmosphere Sounding,CMA,and the Research Centre on Meteorological Observation Engineering Technology,CMA(Grant No.U2021Z05).
文摘Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.
基金supported by the National Natural Science Foundation of China(61771372,61771367,62101494)the National Outstanding Youth Science Fund Project(61525105)+1 种基金Shenzhen Science and Technology Program(KQTD20190929172704911)the Aeronautic al Science Foundation of China(2019200M1001)。
文摘In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is followed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.
基金supported by the Stable-Support Scientific Project of the China Research Institute of Radio-wave Propagation(Grant No.A13XXXXWXX)the National Natural Science Foundation of China(Grant Nos.42174210,4207202,and 42188101)the Strategic Pioneer Program on Space Science,Chinese Academy of Sciences(Grant No.XDA15014800)。
文摘The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.
