This study presents finely resolved radar signatures of multiple cyclonic vortices associated with an EF2 tornadic supercell that occurred in Guangzhou on 16 June 2022 and discusses how the mesocyclone formed on the l...This study presents finely resolved radar signatures of multiple cyclonic vortices associated with an EF2 tornadic supercell that occurred in Guangzhou on 16 June 2022 and discusses how the mesocyclone formed on the lee side of mountain.A nearby X-band phased-array radar provides evidence that the mesocyclone was shallow,with a depth generally confined to less than 3 km.The mesocyclonic feature was observed to initiate from near-ground level,driven by the interaction between intensifying cold pool surges and shallow lee-side ambient flows.It was first recognized shortly after the presence of near-ground cyclonic convergence signatures over the leading edges of cold pool outflows.Over the subsequent 17 min,the mesocyclone developed upward,reaching a maximum height of 3 km,and produced a tornado 8min later.Nearly coinciding with the time of tornadogenesis,a noticeable separation of the low-level tornado cyclone from the midlevel mesocyclone was observed.This shift in the vertically oriented vortex tube was likely caused by modifications to the low-level flow due to the complex hilly terrain or by occlusions associated with rear-flank downdrafts.After tornadogenesis,high-resolution X-PAR observations revealed that the lowest-level mesocyclonic signature contracted into a gate-to-gate tornadic vortex signature(TVS)at the tip of hook echoes.Compared to conventional S-band operational weather radars,rapid-scan X-PAR observations indicate that a core diameter threshold of 1.5–2 km could be employed to identify a cyclonically sheared radial velocity couplet as a TVS,potentially extending the lead time for Doppler-based tornado warnings.展开更多
In September 2020,a pioneering observational network of three X-band phased-array radars(XPARs)was established in Xiamen,a subtropical coastal and densely populated city in southeastern China.Statistically,this study ...In September 2020,a pioneering observational network of three X-band phased-array radars(XPARs)was established in Xiamen,a subtropical coastal and densely populated city in southeastern China.Statistically,this study demonstrated that the XPAR network outperforms single S-band radar in revealing the warm-season convective storms in Xiamen in a fine-scale manner.The findings revealed that convective activity in Xiamen is most frequent in the central and northern mountainous regions,with lower frequency observed in the southern coastal areas.The diurnal pattern of convection occurrence exhibited a unimodal distribution,with a peak in the afternoon.The frequent occurrence of convective storms correlates well in both time and space with the active terrain uplift that occurs when the prevailing winds encounter mountainous areas.Notably,September stands apart with a bimodal diurnal pattern,featuring a prominent afternoon peak and a significant secondary peak before midnight.Further examination of dense rain gauge data in Xiamen indicates that high-frequency areas of short-duration heavy rainfall largely coincide with regions of active convective storms,except for a unique rainfall hotspot in southern Xiamen,where moderate convection frequency is accompanied by substantial rainfall.This anomalous rainfall,predominantly nocturnal,appears less influenced by terrain uplift and exhibits higher precipitation efficiency than daytime rainfall.These preliminary findings offer insights into the characteristics of convection occurrence in Xiamen's subtropical coastal environment and hold promise for enhancing the accuracy of convection and precipitation forecasts in similar environments.展开更多
To verify the detection capability of X-band dual-polarization phased-array radar for forest fires,this paper utilizes X-band dual-polarization phased-array radar data,Himawari-8 satellite data,combined with ground me...To verify the detection capability of X-band dual-polarization phased-array radar for forest fires,this paper utilizes X-band dual-polarization phased-array radar data,Himawari-8 satellite data,combined with ground meteorological automatic station data.A case study of a forest fire in Ao Feng Mountain on February 19,2021,was conducted to comparatively analyze the monitoring results from these two remote sensing methods.The results show that both methods exhibit significant features associated with the forest fire process observed and are effective modern methods of forest fire monitoring.The Himawari-8 satellite identified the fire point at 07:10(LST;LST=UTC+8)with subsequent observations every 10 minutes until 10:00,nearly two hours before the fire was fully extinguished.Compared with the satellite,the Xband dual polarization phased array radar detectedthe fire 14 minutes earlier,with an improved temporal resolution of one minute,and was not affected by cloud cover.In the triggering stage,vigorous stage,sustained burning stage,and extinguishing stage of the forest fire,radar characteristic factors including reflectivity(Z),differential reflectivity(ZDR),and correlation coefficient(CC)showed strong correlations with the fire progression.The radar monitoring results were continuous,complete,and precise.In summary,the X-band dual-polarization phased-array radar offers more detailed detection information,shorter detection time interval,and higher detection spatial accuracy.It presents a promising new method for forest fire detection,providing crucial guidance for on-site rescue operations,particularly for small-scale fire events.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
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 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
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
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 for ...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.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
The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflect...The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflectivity observed by GPM Ku PR is compared quantitatively against GR networks from CINRAD of China and NEXRAD of the United States,and the volume matching method is used for spatial matching.Additionally,a novel frequency correction method for all phases as well as precipitation types is used to correct the GPM Ku PR radar frequency to the GR frequency.A total of 20 GRs(including 10 from CINRAD and 10 from NEXRAD)are included in this comparative analysis.The results indicate that,compared with CINRAD matched data,NEXRAD exhibits larger biases in reflectivity when compared with the frequency-corrected Ku PR.The root-mean-square difference for CINRAD is calculated at 2.38 d B,whereas for NEXRAD it is 3.23 d B.The mean bias of CINRAD matched data is-0.16 d B,while the mean bias of NEXRAD is-2.10 d B.The mean standard deviation of bias for CINRAD is 2.15 d B,while for NEXRAD it is 2.29 d B.This study effectively assesses weather radar data in both the United States and China,which is crucial for improving the overall consistency of global precipitation estimates.展开更多
Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike sc...Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike scatterometers and al-timeters,space-borne SAR offers high-resolution images of the ocean,regardless of weather conditions or time of day.SAR imagery provides rich information about the sea surface,capturing complicated dynamic processes in the upper layers of the ocean,particular-ly in relation to tropical cyclones.Over the past four decades,the advantages of SAR have been increasingly recognized,leading to notable marine applications,especially in the development of algorithms for retrieving wind and wave data from SAR images.This study reviews the history,progress,and future outlook of SAR-based monitoring of sea surface wind and waves.In particular,the ap-plicability of various SAR wind and wave algorithms is systematically investigated,with a particular focus on their performance un-der extreme sea conditions.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
Automotive radar has emerged as a critical component in Advanced Driver Assistance Systems(ADAS)and autonomous driving,enabling robust environmental perception through precise range-Doppler and angular measurements.It...Automotive radar has emerged as a critical component in Advanced Driver Assistance Systems(ADAS)and autonomous driving,enabling robust environmental perception through precise range-Doppler and angular measurements.It plays a pivotal role in enhancing road safety by supporting accurate detection and localization of surrounding objects.However,real-world deployment of automotive radar faces significant challenges,including mutual interference among radar units and dense clutter due to multiple dynamic targets,which demand advanced signal processing solutions beyond conventional methodologies.This paper presents a comprehensive review of traditional signal processing techniques and recent advancements specifically designed to address contemporary operational challenges in automotive radar.Emphasis is placed on direction-of-arrival(DoA)estimation algorithms such as Bartlett beamforming,Minimum Variance Distortionless Response(MVDR),Multiple Signal Classification(MUSIC),and Estimation of Signal Parameters via Rotational Invariance Techniques(ESPRIT).Among these,ESPRIT offers superior resolution for multi-target scenarios with reduced computational complexity compared to MUSIC,making it particularly advantageous for real-time applications.Furthermore,the study evaluates state-of-the-art tracking algorithms,including the Kalman Filter(KF),Extended KF(EKF),Unscented KF,and Bayesian filter.EKF is especially suitable for radar systems due to its capability to linearize nonlinear measurement models.The integration of machine learning approaches for target detection and classification is also discussed,highlighting the trade-off between the simplicity of implementation in K-Nearest Neighbors(KNN)and the enhanced accuracy provided by Support Vector Machines(SVM).A brief overview of benchmark radar datasets,performance metrics,and relevant standards is included to support future research.The paper concludes by outlining ongoing challenges and identifying promising research directions in automotive radar signal processing,particularly in the context of increasingly complex traffic scenarios and autonomous navigation systems.展开更多
In order to realize the automatic recognition and classification of cracks with different depths,in this study,several deep convolutional neural networks including AlexNet,ResNet,and DenseNet were employed to identify...In order to realize the automatic recognition and classification of cracks with different depths,in this study,several deep convolutional neural networks including AlexNet,ResNet,and DenseNet were employed to identify and classify cracks at different depths and in various materials.An analysis process for the automatic classification of crack damage was presented.The image dataset used for model training was obtained from scanning experiments on aluminum and titanium alloy plates using an ultrasonic phased-array flaw detector.All models were trained and validated with the dataset;the proposed models were compared using classification precision and loss values.The results show that the automatic recognition and classification of crack depth can be realized by using the deep learning algorithm to analyze the ultrasonic phased array images,and the classification precision of DenseNet is the highest.The problem that ultrasonic damage identification relies on manual experience is solved.展开更多
Existing through-wall human activity recognition methods often rely on Doppler information or reflective signal characteristics of the human body.However,static individuals,lacking prominent motion features,do not gen...Existing through-wall human activity recognition methods often rely on Doppler information or reflective signal characteristics of the human body.However,static individuals,lacking prominent motion features,do not generate Doppler information.Moreover,radar signals experience significant attenuation due to absorption and scattering effects as they penetrate walls,limiting recognition performance.To address these challenges,this study proposes a novel through-wall human activity recognition method based on MIMO radar.Utilizing a MIMO radar operating at 1–2 GHz,we capture activity data of individuals through walls and process it into range-angle maps to represent activity features.To tackle the issue of minimal variation in reflection areas caused by static individuals,a multi-scale activity feature extraction module is designed,capable of extracting effective features from radar signals across multiple scales.Simultaneously,a temporal attention mechanism is employed to extract keyframe information from sequential signals,focusing on critical moments of activity.Furthermore,this study introduces an activity recognition network based on a Deformable Transformer,which efficiently extracts both global and local features from radar signals,delivering precise human posture and activity sequences.In experimental scenarios involving 24 cm-thick brick walls,the proposed method achieves an impressive 97.1%accuracy in activity recognition classification.展开更多
基金supported by the National Key R&D Program of China(2022YFC3004101)the National Natural Science Foundation of China(Grant No.42275006)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant No.2022A1515011814)the China Meteorological Administration Tornado Key Laboratory(Grant No.TKL202302)the Science and Technology Research Project of Guangdong Meteorological Service(Grant No.GRMC2023Q35)。
文摘This study presents finely resolved radar signatures of multiple cyclonic vortices associated with an EF2 tornadic supercell that occurred in Guangzhou on 16 June 2022 and discusses how the mesocyclone formed on the lee side of mountain.A nearby X-band phased-array radar provides evidence that the mesocyclone was shallow,with a depth generally confined to less than 3 km.The mesocyclonic feature was observed to initiate from near-ground level,driven by the interaction between intensifying cold pool surges and shallow lee-side ambient flows.It was first recognized shortly after the presence of near-ground cyclonic convergence signatures over the leading edges of cold pool outflows.Over the subsequent 17 min,the mesocyclone developed upward,reaching a maximum height of 3 km,and produced a tornado 8min later.Nearly coinciding with the time of tornadogenesis,a noticeable separation of the low-level tornado cyclone from the midlevel mesocyclone was observed.This shift in the vertically oriented vortex tube was likely caused by modifications to the low-level flow due to the complex hilly terrain or by occlusions associated with rear-flank downdrafts.After tornadogenesis,high-resolution X-PAR observations revealed that the lowest-level mesocyclonic signature contracted into a gate-to-gate tornadic vortex signature(TVS)at the tip of hook echoes.Compared to conventional S-band operational weather radars,rapid-scan X-PAR observations indicate that a core diameter threshold of 1.5–2 km could be employed to identify a cyclonically sheared radial velocity couplet as a TVS,potentially extending the lead time for Doppler-based tornado warnings.
基金Natural Science Foundation of Fujian Province(2023J011338)Guided Foundation of Xiamen Science and Technology Bureau(3502Z20214ZD4009,3502Z20214ZD4010)+1 种基金Key Projects of East China Phased Array Weather Radar Application Joint Laboratory(EPJL_RP2025010)National Natural Science Foundation of China(41905049)。
文摘In September 2020,a pioneering observational network of three X-band phased-array radars(XPARs)was established in Xiamen,a subtropical coastal and densely populated city in southeastern China.Statistically,this study demonstrated that the XPAR network outperforms single S-band radar in revealing the warm-season convective storms in Xiamen in a fine-scale manner.The findings revealed that convective activity in Xiamen is most frequent in the central and northern mountainous regions,with lower frequency observed in the southern coastal areas.The diurnal pattern of convection occurrence exhibited a unimodal distribution,with a peak in the afternoon.The frequent occurrence of convective storms correlates well in both time and space with the active terrain uplift that occurs when the prevailing winds encounter mountainous areas.Notably,September stands apart with a bimodal diurnal pattern,featuring a prominent afternoon peak and a significant secondary peak before midnight.Further examination of dense rain gauge data in Xiamen indicates that high-frequency areas of short-duration heavy rainfall largely coincide with regions of active convective storms,except for a unique rainfall hotspot in southern Xiamen,where moderate convection frequency is accompanied by substantial rainfall.This anomalous rainfall,predominantly nocturnal,appears less influenced by terrain uplift and exhibits higher precipitation efficiency than daytime rainfall.These preliminary findings offer insights into the characteristics of convection occurrence in Xiamen's subtropical coastal environment and hold promise for enhancing the accuracy of convection and precipitation forecasts in similar environments.
基金National Key R&D Program of China(2022YFC3004101)Guangdong Basic and Applied Basic Research Foundation(2023A1515011971)+3 种基金Science and Tech-nology Projects in Guangzhou(2023B04J0232)Science and Technology Development Fund Project of Guangdong Meteor-ological Bureau(GRMC2022Q23,GRMC2022Q01)Jiangmen Basic and Applied Basic Research Key Programs(202312)Science and Technology Development Fund Project of Jiangmen Meteorological Bureau(202008,202004,201907,202007,201704)。
文摘To verify the detection capability of X-band dual-polarization phased-array radar for forest fires,this paper utilizes X-band dual-polarization phased-array radar data,Himawari-8 satellite data,combined with ground meteorological automatic station data.A case study of a forest fire in Ao Feng Mountain on February 19,2021,was conducted to comparatively analyze the monitoring results from these two remote sensing methods.The results show that both methods exhibit significant features associated with the forest fire process observed and are effective modern methods of forest fire monitoring.The Himawari-8 satellite identified the fire point at 07:10(LST;LST=UTC+8)with subsequent observations every 10 minutes until 10:00,nearly two hours before the fire was fully extinguished.Compared with the satellite,the Xband dual polarization phased array radar detectedthe fire 14 minutes earlier,with an improved temporal resolution of one minute,and was not affected by cloud cover.In the triggering stage,vigorous stage,sustained burning stage,and extinguishing stage of the forest fire,radar characteristic factors including reflectivity(Z),differential reflectivity(ZDR),and correlation coefficient(CC)showed strong correlations with the fire progression.The radar monitoring results were continuous,complete,and precise.In summary,the X-band dual-polarization phased-array radar offers more detailed detection information,shorter detection time interval,and higher detection spatial accuracy.It presents a promising new method for forest fire detection,providing crucial guidance for on-site rescue operations,particularly for small-scale fire events.
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 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 National Nature Science Founda tion of China(50099620)863 Project(2001AA132050-03)
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.
基金Foundation item:Supported by the National Nature Science Founda-tion of China(50099620)and 863 Program Foundation of China(2001AA132050-03)
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.
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funded by the National Key Research and Development Program of China(Grant No.2023YFB3907500)the National Natural Science Foundation(Grant No.42330602)the“Fengyun Satellite Remote Sensing Product Validation and Verification”Youth Innovation Team of the China Meteorological Administration(Grant No.CMA2023QN12)。
文摘The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflectivity observed by GPM Ku PR is compared quantitatively against GR networks from CINRAD of China and NEXRAD of the United States,and the volume matching method is used for spatial matching.Additionally,a novel frequency correction method for all phases as well as precipitation types is used to correct the GPM Ku PR radar frequency to the GR frequency.A total of 20 GRs(including 10 from CINRAD and 10 from NEXRAD)are included in this comparative analysis.The results indicate that,compared with CINRAD matched data,NEXRAD exhibits larger biases in reflectivity when compared with the frequency-corrected Ku PR.The root-mean-square difference for CINRAD is calculated at 2.38 d B,whereas for NEXRAD it is 3.23 d B.The mean bias of CINRAD matched data is-0.16 d B,while the mean bias of NEXRAD is-2.10 d B.The mean standard deviation of bias for CINRAD is 2.15 d B,while for NEXRAD it is 2.29 d B.This study effectively assesses weather radar data in both the United States and China,which is crucial for improving the overall consistency of global precipitation estimates.
基金supported by the National Nat-ural Science Foundation of China(No.42376174)the Natural Science Foundation of Shanghai(No.23ZR 1426900).
文摘Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike scatterometers and al-timeters,space-borne SAR offers high-resolution images of the ocean,regardless of weather conditions or time of day.SAR imagery provides rich information about the sea surface,capturing complicated dynamic processes in the upper layers of the ocean,particular-ly in relation to tropical cyclones.Over the past four decades,the advantages of SAR have been increasingly recognized,leading to notable marine applications,especially in the development of algorithms for retrieving wind and wave data from SAR images.This study reviews the history,progress,and future outlook of SAR-based monitoring of sea surface wind and waves.In particular,the ap-plicability of various SAR wind and wave algorithms is systematically investigated,with a particular focus on their performance un-der extreme sea conditions.
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 in part by the National Science and Technology Council,Taiwan:NSTC 113-2410-H-030-077-MY2.
文摘Automotive radar has emerged as a critical component in Advanced Driver Assistance Systems(ADAS)and autonomous driving,enabling robust environmental perception through precise range-Doppler and angular measurements.It plays a pivotal role in enhancing road safety by supporting accurate detection and localization of surrounding objects.However,real-world deployment of automotive radar faces significant challenges,including mutual interference among radar units and dense clutter due to multiple dynamic targets,which demand advanced signal processing solutions beyond conventional methodologies.This paper presents a comprehensive review of traditional signal processing techniques and recent advancements specifically designed to address contemporary operational challenges in automotive radar.Emphasis is placed on direction-of-arrival(DoA)estimation algorithms such as Bartlett beamforming,Minimum Variance Distortionless Response(MVDR),Multiple Signal Classification(MUSIC),and Estimation of Signal Parameters via Rotational Invariance Techniques(ESPRIT).Among these,ESPRIT offers superior resolution for multi-target scenarios with reduced computational complexity compared to MUSIC,making it particularly advantageous for real-time applications.Furthermore,the study evaluates state-of-the-art tracking algorithms,including the Kalman Filter(KF),Extended KF(EKF),Unscented KF,and Bayesian filter.EKF is especially suitable for radar systems due to its capability to linearize nonlinear measurement models.The integration of machine learning approaches for target detection and classification is also discussed,highlighting the trade-off between the simplicity of implementation in K-Nearest Neighbors(KNN)and the enhanced accuracy provided by Support Vector Machines(SVM).A brief overview of benchmark radar datasets,performance metrics,and relevant standards is included to support future research.The paper concludes by outlining ongoing challenges and identifying promising research directions in automotive radar signal processing,particularly in the context of increasingly complex traffic scenarios and autonomous navigation systems.
基金supported by the National Natural Science Foundation of China(Nos.52222504 and 52241502)the Natural Science Talents Foundation of Shaanxi Province(No.2021JC-04).
文摘In order to realize the automatic recognition and classification of cracks with different depths,in this study,several deep convolutional neural networks including AlexNet,ResNet,and DenseNet were employed to identify and classify cracks at different depths and in various materials.An analysis process for the automatic classification of crack damage was presented.The image dataset used for model training was obtained from scanning experiments on aluminum and titanium alloy plates using an ultrasonic phased-array flaw detector.All models were trained and validated with the dataset;the proposed models were compared using classification precision and loss values.The results show that the automatic recognition and classification of crack depth can be realized by using the deep learning algorithm to analyze the ultrasonic phased array images,and the classification precision of DenseNet is the highest.The problem that ultrasonic damage identification relies on manual experience is solved.
基金supported by National Natural Science Foundation of China(No.62272242)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Nos.KYCX21_0800,KYCX23_1082).
文摘Existing through-wall human activity recognition methods often rely on Doppler information or reflective signal characteristics of the human body.However,static individuals,lacking prominent motion features,do not generate Doppler information.Moreover,radar signals experience significant attenuation due to absorption and scattering effects as they penetrate walls,limiting recognition performance.To address these challenges,this study proposes a novel through-wall human activity recognition method based on MIMO radar.Utilizing a MIMO radar operating at 1–2 GHz,we capture activity data of individuals through walls and process it into range-angle maps to represent activity features.To tackle the issue of minimal variation in reflection areas caused by static individuals,a multi-scale activity feature extraction module is designed,capable of extracting effective features from radar signals across multiple scales.Simultaneously,a temporal attention mechanism is employed to extract keyframe information from sequential signals,focusing on critical moments of activity.Furthermore,this study introduces an activity recognition network based on a Deformable Transformer,which efficiently extracts both global and local features from radar signals,delivering precise human posture and activity sequences.In experimental scenarios involving 24 cm-thick brick walls,the proposed method achieves an impressive 97.1%accuracy in activity recognition classification.
