When multiple ground-based radars(GB-rads)are utilized together to resolve three-dimensional(3-D)deformations,the resolving accuracy is related with the measurement geometry constructed by these radars.This paper focu...When multiple ground-based radars(GB-rads)are utilized together to resolve three-dimensional(3-D)deformations,the resolving accuracy is related with the measurement geometry constructed by these radars.This paper focuses on constrained geometry analysis to resolve 3-D deformations from three GB-rads.The geometric dilution of precision(GDOP)is utilized to evaluate 3-D deformation accuracy of a single target,and its theoretical equation is derived by building a simplified 3-D coordinate system.Then for a 3-D scene,its optimal accuracy problem is converted into determining the minimum value of an objective function with a boundary constraint.The genetic algorithm is utilized to solve this constrained optimization problem.Numerical simulations are made to validate the correctness of the theoretical analysis results.展开更多
A prototype space-based cloud radar has been a precipitation system over Tianjin, China in July developed and was installed on an airplane to observe 2010. Ground-based S-band and Ka-band radars were used to examine t...A prototype space-based cloud radar has been a precipitation system over Tianjin, China in July developed and was installed on an airplane to observe 2010. Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype. A cross-comparison algorithm between different wavelengths, spatial resolutions and platform radars is presented. The reflectivity biases, correlation coefficients and standard deviations between the radars are analyzed. The equivalent reflectivity bias between the S- and Ka-band radars were simulated with a given raindrop size distribution. The results indicated that reflectivity bias between the S- and Ka-band radars due to scattering properties was less than 5 dB, and for weak precipitation the bias was negligible. The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity, but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter. The measured refiectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar (SA radar), and 13.7 dB stronger than that by the ground-based cloud radar. The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar. This study could provide a method for the quantitative examination of the observation ability for space-based radars.展开更多
During the 21st Chinese National Antarctic Research Expedition(CHINARE 21,2004/05),a radar dataset was collected using a ground-based radar system,along a traverse line from Zhongshan Station to DT401(130 km from the ...During the 21st Chinese National Antarctic Research Expedition(CHINARE 21,2004/05),a radar dataset was collected using a ground-based radar system,along a traverse line from Zhongshan Station to DT401(130 km from the Kunlun station).The internal layering structure and subglacial conditions were revealed along the radar profi le.Continuous internal layers,disturbed layers,and echo-free zones(EFZs)along the profi le were identifi ed and classifi ed,and the spatial distribution was presented.Based on recent surface ice velocity data,we found that the internal layers at a depth of 200-300 m in the upper ice sheet are continuous,smooth,and nearly parallel to the ice surface topography.In addition,the thick band of continuous layers changes little with increasing latitude.At depths below 300 m,the geometric structure of the internal layers and the vertical width of the EFZ band are infl uenced by the surface ice velocity and bed topography.The relatively high disturbance,layer discontinuity,and larger EFZ band width directly correspond to a higher surface ice velocity and a sharper bed topography.In particular,we found that at a depth of 650-950 km,the Lambert Glacier Rift in the Gamburtsev Mountains has a higher ice fl ow;moreover,the revealed internal layers are disturbed or broken,and the maximal vertical width of the EFZ band most likely exceeds 2000 m.展开更多
Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in p...Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table(LUT) of effective cloud water content(ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness(CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar(MMCR) measurements, and results show that the mean bias(correlation coefficient) is0.18±1.79 km(0.73), which is lower(higher) than 0.23±2.11 km(0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar(i.e., Cloud Sat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.展开更多
The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplane...The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplanetary magnetic field conditions,and simultaneously monitor the auroral response of the Northern Hemisphere ionosphere.Combining these large-scale responses with medium and fine-scale measurements at a variety of cadences by additional ground-based and space-based instruments will enable a much greater scientific impact beyond the original goals of the SMILE mission.Here,we describe current community efforts to prepare for SMILE,and the benefits and context various experiments that have explicitly expressed support for SMILE can offer.A dedicated group of international scientists representing many different experiment types and geographical locations,the Ground-based and Additional Science Working Group,is facilitating these efforts.Preparations include constructing an online SMILE Data Fusion Facility,the discussion of particular or special modes for experiments such as coherent and incoherent scatter radar,and the consideration of particular observing strategies and spacecraft conjunctions.We anticipate growing interest and community engagement with the SMILE mission,and we welcome novel ideas and insights from the solar-terrestrial community.展开更多
In order to explain theoretically the observational biases of reflectivity and structure of precipitation systems by TRMM Precipitation Radar (TRMM PR) and ground-based radar,the effects of wavelengths,incident direct...In order to explain theoretically the observational biases of reflectivity and structure of precipitation systems by TRMM Precipitation Radar (TRMM PR) and ground-based radar,the effects of wavelengths,incident direction of radar waves and radar beam width on the reflectivity observation are simulated.The results show that the error due to the different wavelength and incident direction of radar wave is within 2.0 dB,TRMM PR can observe a larger reflectivity than ground-based radar in echo center.TRMM PR smoothes the cloud structure,overestimates and underestimates reflectivity by 3-5 dB in strong and week echo areas,respectively.Beam width and long distance from TRMM PR to target cause it to overestimate the large echo area and area integrated rainfall amount,and to underestimate the averaged refleetivity.The theoretical results above can only explain part of observational facts,meaning that the comparison of observation results between TRMM PR and ground-based radar is complicated,the attenuation of radar wave within precipitation area is the main factor to affect the observed result.展开更多
Measurements of carbon dioxide(CO_(2)),methane(CH_(4)),and carbon monoxide(CO)are of great importance in the Qinghai-Tibetan region,as it is the highest and largest plateau in the world affecting global weather and cl...Measurements of carbon dioxide(CO_(2)),methane(CH_(4)),and carbon monoxide(CO)are of great importance in the Qinghai-Tibetan region,as it is the highest and largest plateau in the world affecting global weather and climate systems.In this study,for the first time,we present CO_(2),CH_(4),and CO column measurements carried out by a Bruker EM27/SUN Fourier-transform infrared spectrometer(FTIR)at Golmud(36.42°E,94.91°N,2808 m)in August 2021.The mean and standard deviation of the column-average dry-air mixing ratio of CO_(2),CH_(4),and CO(XCO_(2),XCH_(4),and XCO)are 409.3±0.4 ppm,1905.5±19.4 ppb,and 103.1±7.7 ppb,respectively.The differences between the FTIR co-located TROPOMI/S5P satellite measurements at Golmud are 0.68±0.64%(13.1±12.2 ppb)for XCH_(4) and 9.81±3.48%(–10.7±3.8 ppb)for XCO,which are within their retrieval uncertainties.High correlations for both XCH_(4) and XCO are observed between the FTIR and S5P satellite measurements.Using the FLEXPART model and satellite measurements,we find that enhanced CH_(4) and CO columns in Golmud are affected by anthropogenic emissions transported from North India.This study provides an insight into the variations of the CO_(2),CH_(4),and CO columns in the Qinghai-Tibetan Plateau.展开更多
In order to improve understanding of deep convective clouds over the Tibetan Plateau, characteristics of vertical structure of a deep strong convective cloud over Naqu station and a deep weak convective cloud approxim...In order to improve understanding of deep convective clouds over the Tibetan Plateau, characteristics of vertical structure of a deep strong convective cloud over Naqu station and a deep weak convective cloud approximately 100 km to the west of Naqu station, which occurred over 1300-1600 Beijing Time (BT) 9 July 2014 during the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-Ⅲ), are analyzed, based on multi-source satellite data from TRMM, CloudSat, and Aqua, and radar data from ground-based vertically pointing radars (C-band frequency-modulated continuous-wave radar and KA-band millimeter wave cloud radar). The results are as follows.(1) The horizontal scales of both the deep strong and deep weak convective clouds were small (10-20 km), and their tops were high[15-16 km above sea level (ASL)]. Across the level of 0℃ isotherm in the deep strong convective cloud, the reflectivity increased rapidly, suggesting that the melting process of solid precipitation particles through the 0℃ level played an important role. A bright band located at 5.5 km ASL (i.e., 1 km above ground level) appeared during the period of convection weakening.(2) The reflectivity values from TRMM precipitation radar below 11 km were found to be overestimated compared to those derived from the C-band frequency-modulated continuous-wave radar.(3) Deep convective clouds were mainly ice clouds, and there were rich small ice particles above 10 km, while few large ice particles were found below 10 km. The microphysical processes of deep strong and deep weak convective clouds mainly included mixed-phase process and glaciated process, and the mixed-phase process can be divided into two types:one was the rimming process below the level of -25℃(deep strong convective cloud) or -29℃(deep weak convective cloud) and the other was aggregation and deposition process above that level. The latter process was accompanied with fast increase in ice particle effective radius. The above evidence from space-based and ground-based observational data further clarify the characteristics of vertical structure of deep convective clouds over the Tibetan Plateau, and provide a basis for the evaluation of simulation results of deep convective clouds by cloud models.展开更多
The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high reso...The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of asteroids.The ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant troposphere.Traditional spatiotemporal freezing tropospheric models are ineffective.To cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of asteroids.For the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background troposphere.For the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase screen.Through simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.展开更多
The accuracy of passive satellite cloud top height (CTH) retrieval shows regional dependence. This paper assesses the CTH derived from the FY-4A and Himawari-8 satellites through comparison with those from the ground-...The accuracy of passive satellite cloud top height (CTH) retrieval shows regional dependence. This paper assesses the CTH derived from the FY-4A and Himawari-8 satellites through comparison with those from the ground-based millimeter radar at two sites: Yangbajing, Tibet, China (YBJ), and the Institute of Atmospheric Physics (IAP), Beijing, China. The comparison shows that Himawari-8 missed more CTHs at night than FY-4A, especially at YBJ. It is found that the CTH difference (CTHD;radar CTH minus satellite CTH) for FY-4A and Himawari-8 is 0.06 ± 1.90 km and −0.02 ± 2.40 km at YBJ respectively, and that is 0.93 ± 2.24 km and 0.99 ± 2.37 km at IAP respectively. The discrepancy between the satellites and radar at IAP is larger than that at YBJ. Both satellites show better performance for mid-level and low-level clouds than for high-level clouds at the two sites. The retrievals from FY-4A agree well with those from Himawari-8, with a mean difference of 0.08 km at YBJ and 0.06 km at IAP. It is found that the CTHD decreases as the cloud depth increases at both sites. However, the CTHD has no obvious dependence on cloud layers and fractions. Investigations show that aerosol concentration has little impact on the CTHD. For high and thin clouds, the CTHD increases gradually with the increase of the surface temperature, which might be a key factor causing the regional discrepancy between IAP and YBJ.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
In recent years, ground-based micro-deformation monitoring radar has attracted much attention due to its excellent monitoring capability. By controlling the repeated campaigns of the radar antenna on a fixed track, gr...In recent years, ground-based micro-deformation monitoring radar has attracted much attention due to its excellent monitoring capability. By controlling the repeated campaigns of the radar antenna on a fixed track, ground-based micro-deformation monitoring radar can accomplish repeat-pass interferometry without a space baseline and thus obtain highprecision deformation data of a large scene at one time. However, it is difficult to guarantee absolute stable installation position in every campaign. If the installation position is unstable, the stability of the radar track will be affected randomly, resulting in time-varying baseline error. In this study, a correction method for this error is developed by analyzing the error distribution law while the spatial baseline is unknown. In practice, the error data are first identified by frequency components, then the data of each one-dimensional array(in azimuth direction or range direction) are grouped based on numerical distribution period, and finally the error is corrected by the nonlinear model established with each group.This method is verified with measured data from a slope in southern China, and the results show that the method can effectively correct the time-varying baseline error caused by rail instability and effectively improve the monitoring data accuracy of groundbased micro-deformation radar in short term and long term.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
Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be co...Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.展开更多
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
There is a growing body of research on the swarm unmanned aerial vehicle(UAV)in recent years,which has the characteristics of small,low speed,and low height as radar target.To confront the swarm UAV,the design of anti...There is a growing body of research on the swarm unmanned aerial vehicle(UAV)in recent years,which has the characteristics of small,low speed,and low height as radar target.To confront the swarm UAV,the design of anti-UAV radar system based on multiple input multiple output(MIMO)is put forward,which can elevate the performance of resolution,angle accuracy,high data rate,and tracking flexibility for swarm UAV detection.Target resolution and detection are the core problem in detecting the swarm UAV.The distinct advantage of MIMO system in angular accuracy measurement is demonstrated by comparing MIMO radar with phased array radar.Since MIMO radar has better performance in resolution,swarm UAV detection still has difficulty in target detection.This paper proposes a multi-mode data fusion algorithm based on deep neural networks to improve the detection effect.Subsequently,signal processing and data processing based on the detection fusion algorithm above are designed,forming a high resolution detection loop.Several simulations are designed to illustrate the feasibility of the designed system and the proposed algorithm.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
Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental perception.However,existing algorithms based on discrete Fourier transform(DFT),multiple signal c...Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental perception.However,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(MUSIC)and compressed sensing,etc.,cannot achieve both low complexity and high resolution simultaneously.This paper proposes an efficient 2-D MUSIC algorithm for super-resolution target estimation/tracking based on FMCW radar.Firstly,we enhance the efficiency of 2-D MUSIC azimuth-range spectrum estimation by incorporating 2-D DFT and multi-level resolution searching strategy.Secondly,we apply the gradient descent method to tightly integrate the spatial continuity of object motion into spectrum estimation when processing multi-epoch radar data,which improves the efficiency of continuous target tracking.These two approaches have improved the algorithm efficiency by nearly 2-4 orders of magnitude without losing accuracy and resolution.Simulation experiments are conducted to validate the effectiveness of the algorithm in both single-epoch estimation and multi-epoch tracking scenarios.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
The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic reconnaissance.Existing methodologies predominantly rely on prior information or heavily constrai...The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic reconnaissance.Existing methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative applications.This paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse trains.Simulation results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.展开更多
基金supported by the National Natural Science Foundation of China(61960206009,61971037,31727901)the Natural Science Foundation of Chongqing+1 种基金China(2020jcyj-jq X0008)Chongqing Key Laboratory of Geological Environment Monitoring and Disaster Early-warning in Three Gorges Reservoir Area(ZD2020A0101)。
文摘When multiple ground-based radars(GB-rads)are utilized together to resolve three-dimensional(3-D)deformations,the resolving accuracy is related with the measurement geometry constructed by these radars.This paper focuses on constrained geometry analysis to resolve 3-D deformations from three GB-rads.The geometric dilution of precision(GDOP)is utilized to evaluate 3-D deformation accuracy of a single target,and its theoretical equation is derived by building a simplified 3-D coordinate system.Then for a 3-D scene,its optimal accuracy problem is converted into determining the minimum value of an objective function with a boundary constraint.The genetic algorithm is utilized to solve this constrained optimization problem.Numerical simulations are made to validate the correctness of the theoretical analysis results.
基金the Chinese Academy of Meteorological Sciences Basic Scientific and Operational Project(observation and retrieval methods of microphysics and dynamic parameters of cloud and precipitation with multi-wavelength remote sensing)the National Key Program for Developing Basic Sciences under Grant 2012CB417202+1 种基金the Meteorological Special Project(study and data process and key technology for space-borne precipitation radar)the National Natural Science Foundation of China(Grant Nos.40775021 and 41075098)
文摘A prototype space-based cloud radar has been a precipitation system over Tianjin, China in July developed and was installed on an airplane to observe 2010. Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype. A cross-comparison algorithm between different wavelengths, spatial resolutions and platform radars is presented. The reflectivity biases, correlation coefficients and standard deviations between the radars are analyzed. The equivalent reflectivity bias between the S- and Ka-band radars were simulated with a given raindrop size distribution. The results indicated that reflectivity bias between the S- and Ka-band radars due to scattering properties was less than 5 dB, and for weak precipitation the bias was negligible. The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity, but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter. The measured refiectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar (SA radar), and 13.7 dB stronger than that by the ground-based cloud radar. The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar. This study could provide a method for the quantitative examination of the observation ability for space-based radars.
基金This research is supported by the Funded by the Natural Science Foundation of China(41876230,41376192)the Major National Scientifi c Research Project on Global Changes(973 Project)(2013CBA01804)Comprehensive Investigation&Assessment Programs(CHINARE2017-01-01).
文摘During the 21st Chinese National Antarctic Research Expedition(CHINARE 21,2004/05),a radar dataset was collected using a ground-based radar system,along a traverse line from Zhongshan Station to DT401(130 km from the Kunlun station).The internal layering structure and subglacial conditions were revealed along the radar profi le.Continuous internal layers,disturbed layers,and echo-free zones(EFZs)along the profi le were identifi ed and classifi ed,and the spatial distribution was presented.Based on recent surface ice velocity data,we found that the internal layers at a depth of 200-300 m in the upper ice sheet are continuous,smooth,and nearly parallel to the ice surface topography.In addition,the thick band of continuous layers changes little with increasing latitude.At depths below 300 m,the geometric structure of the internal layers and the vertical width of the EFZ band are infl uenced by the surface ice velocity and bed topography.The relatively high disturbance,layer discontinuity,and larger EFZ band width directly correspond to a higher surface ice velocity and a sharper bed topography.In particular,we found that at a depth of 650-950 km,the Lambert Glacier Rift in the Gamburtsev Mountains has a higher ice fl ow;moreover,the revealed internal layers are disturbed or broken,and the maximal vertical width of the EFZ band most likely exceeds 2000 m.
基金funded by the National Natural Science Foundation of China (Grant Nos. 42305150 and 42325501)the China Postdoctoral Science Foundation (Grant No. 2023M741774)。
文摘Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table(LUT) of effective cloud water content(ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness(CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar(MMCR) measurements, and results show that the mean bias(correlation coefficient) is0.18±1.79 km(0.73), which is lower(higher) than 0.23±2.11 km(0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar(i.e., Cloud Sat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.
基金supported by Royal Society grant DHFR1211068funded by UKSA+14 种基金STFCSTFC grant ST/M001083/1funded by STFC grant ST/W00089X/1supported by NERC grant NE/W003309/1(E3d)funded by NERC grant NE/V000748/1support from NERC grants NE/V015133/1,NE/R016038/1(BAS magnetometers),and grants NE/R01700X/1 and NE/R015848/1(EISCAT)supported by NERC grant NE/T000937/1NSFC grants 42174208 and 41821003supported by the Research Council of Norway grant 223252PRODEX arrangement 4000123238 from the European Space Agencysupport of the AUTUMN East-West magnetometer network by the Canadian Space Agencysupported by NASA’s Heliophysics U.S.Participating Investigator Programsupport from grant NSF AGS 2027210supported by grant Dnr:2020-00106 from the Swedish National Space Agencysupported by the German Research Foundation(DFG)under number KR 4375/2-1 within SPP"Dynamic Earth"。
文摘The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplanetary magnetic field conditions,and simultaneously monitor the auroral response of the Northern Hemisphere ionosphere.Combining these large-scale responses with medium and fine-scale measurements at a variety of cadences by additional ground-based and space-based instruments will enable a much greater scientific impact beyond the original goals of the SMILE mission.Here,we describe current community efforts to prepare for SMILE,and the benefits and context various experiments that have explicitly expressed support for SMILE can offer.A dedicated group of international scientists representing many different experiment types and geographical locations,the Ground-based and Additional Science Working Group,is facilitating these efforts.Preparations include constructing an online SMILE Data Fusion Facility,the discussion of particular or special modes for experiments such as coherent and incoherent scatter radar,and the consideration of particular observing strategies and spacecraft conjunctions.We anticipate growing interest and community engagement with the SMILE mission,and we welcome novel ideas and insights from the solar-terrestrial community.
基金the Project of National Fundamental Research Planning"Research on the formation mechanism and the prediction theory of hazardous weather over China"(G1998040909)Doctoral Start-up Foundation Project in Chinese Academy of Meteorological Sciences
文摘In order to explain theoretically the observational biases of reflectivity and structure of precipitation systems by TRMM Precipitation Radar (TRMM PR) and ground-based radar,the effects of wavelengths,incident direction of radar waves and radar beam width on the reflectivity observation are simulated.The results show that the error due to the different wavelength and incident direction of radar wave is within 2.0 dB,TRMM PR can observe a larger reflectivity than ground-based radar in echo center.TRMM PR smoothes the cloud structure,overestimates and underestimates reflectivity by 3-5 dB in strong and week echo areas,respectively.Beam width and long distance from TRMM PR to target cause it to overestimate the large echo area and area integrated rainfall amount,and to underestimate the averaged refleetivity.The theoretical results above can only explain part of observational facts,meaning that the comparison of observation results between TRMM PR and ground-based radar is complicated,the attenuation of radar wave within precipitation area is the main factor to affect the observed result.
基金supported by the National Natural Science Foundation of China(Grant No.42205140,41975035)the National Key Research and Development Program of China(2021YFB3901000).
文摘Measurements of carbon dioxide(CO_(2)),methane(CH_(4)),and carbon monoxide(CO)are of great importance in the Qinghai-Tibetan region,as it is the highest and largest plateau in the world affecting global weather and climate systems.In this study,for the first time,we present CO_(2),CH_(4),and CO column measurements carried out by a Bruker EM27/SUN Fourier-transform infrared spectrometer(FTIR)at Golmud(36.42°E,94.91°N,2808 m)in August 2021.The mean and standard deviation of the column-average dry-air mixing ratio of CO_(2),CH_(4),and CO(XCO_(2),XCH_(4),and XCO)are 409.3±0.4 ppm,1905.5±19.4 ppb,and 103.1±7.7 ppb,respectively.The differences between the FTIR co-located TROPOMI/S5P satellite measurements at Golmud are 0.68±0.64%(13.1±12.2 ppb)for XCH_(4) and 9.81±3.48%(–10.7±3.8 ppb)for XCO,which are within their retrieval uncertainties.High correlations for both XCH_(4) and XCO are observed between the FTIR and S5P satellite measurements.Using the FLEXPART model and satellite measurements,we find that enhanced CH_(4) and CO columns in Golmud are affected by anthropogenic emissions transported from North India.This study provides an insight into the variations of the CO_(2),CH_(4),and CO columns in the Qinghai-Tibetan Plateau.
基金Supported by the China Meteorological Administration Special Public Welfare Research Fund for the Third Tibetan Plateau Atmospheric Science Experiment(GYHY201406001)National Natural Science Foundation of China(41605107 and 91437104)Basic Research Fund of Chinese Academy of Meteorological Sciences(2015Y006)
文摘In order to improve understanding of deep convective clouds over the Tibetan Plateau, characteristics of vertical structure of a deep strong convective cloud over Naqu station and a deep weak convective cloud approximately 100 km to the west of Naqu station, which occurred over 1300-1600 Beijing Time (BT) 9 July 2014 during the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-Ⅲ), are analyzed, based on multi-source satellite data from TRMM, CloudSat, and Aqua, and radar data from ground-based vertically pointing radars (C-band frequency-modulated continuous-wave radar and KA-band millimeter wave cloud radar). The results are as follows.(1) The horizontal scales of both the deep strong and deep weak convective clouds were small (10-20 km), and their tops were high[15-16 km above sea level (ASL)]. Across the level of 0℃ isotherm in the deep strong convective cloud, the reflectivity increased rapidly, suggesting that the melting process of solid precipitation particles through the 0℃ level played an important role. A bright band located at 5.5 km ASL (i.e., 1 km above ground level) appeared during the period of convection weakening.(2) The reflectivity values from TRMM precipitation radar below 11 km were found to be overestimated compared to those derived from the C-band frequency-modulated continuous-wave radar.(3) Deep convective clouds were mainly ice clouds, and there were rich small ice particles above 10 km, while few large ice particles were found below 10 km. The microphysical processes of deep strong and deep weak convective clouds mainly included mixed-phase process and glaciated process, and the mixed-phase process can be divided into two types:one was the rimming process below the level of -25℃(deep strong convective cloud) or -29℃(deep weak convective cloud) and the other was aggregation and deposition process above that level. The latter process was accompanied with fast increase in ice particle effective radius. The above evidence from space-based and ground-based observational data further clarify the characteristics of vertical structure of deep convective clouds over the Tibetan Plateau, and provide a basis for the evaluation of simulation results of deep convective clouds by cloud models.
基金supported in part by the National Natural Science Foundation of China(Nos.62101039,62201051)in part by the Shandong Excellent Young Scientists Fund Program(Overseas)in part by China Postdoctoral Science Foundation(No.2022M720443).
文摘The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of asteroids.The ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant troposphere.Traditional spatiotemporal freezing tropospheric models are ineffective.To cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of asteroids.For the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background troposphere.For the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase screen.Through simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.
基金This work was funded by the National Natural Science Found-ation of China(Grant Nos.41775032 and 41275040).
文摘The accuracy of passive satellite cloud top height (CTH) retrieval shows regional dependence. This paper assesses the CTH derived from the FY-4A and Himawari-8 satellites through comparison with those from the ground-based millimeter radar at two sites: Yangbajing, Tibet, China (YBJ), and the Institute of Atmospheric Physics (IAP), Beijing, China. The comparison shows that Himawari-8 missed more CTHs at night than FY-4A, especially at YBJ. It is found that the CTH difference (CTHD;radar CTH minus satellite CTH) for FY-4A and Himawari-8 is 0.06 ± 1.90 km and −0.02 ± 2.40 km at YBJ respectively, and that is 0.93 ± 2.24 km and 0.99 ± 2.37 km at IAP respectively. The discrepancy between the satellites and radar at IAP is larger than that at YBJ. Both satellites show better performance for mid-level and low-level clouds than for high-level clouds at the two sites. The retrievals from FY-4A agree well with those from Himawari-8, with a mean difference of 0.08 km at YBJ and 0.06 km at IAP. It is found that the CTHD decreases as the cloud depth increases at both sites. However, the CTHD has no obvious dependence on cloud layers and fractions. Investigations show that aerosol concentration has little impact on the CTHD. For high and thin clouds, the CTHD increases gradually with the increase of the surface temperature, which might be a key factor causing the regional discrepancy between IAP and YBJ.
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 National Key R&D Program of China (2018YFC1508502)the National Natural Science Foundation of China (41601569,61661043,61631011)the Science and Technology Innovation Guidance Project of Inner Mongolia Autonomous Region (2019GG139,KCBJ2017,KCBJ 2018014,2019ZD022)。
文摘In recent years, ground-based micro-deformation monitoring radar has attracted much attention due to its excellent monitoring capability. By controlling the repeated campaigns of the radar antenna on a fixed track, ground-based micro-deformation monitoring radar can accomplish repeat-pass interferometry without a space baseline and thus obtain highprecision deformation data of a large scene at one time. However, it is difficult to guarantee absolute stable installation position in every campaign. If the installation position is unstable, the stability of the radar track will be affected randomly, resulting in time-varying baseline error. In this study, a correction method for this error is developed by analyzing the error distribution law while the spatial baseline is unknown. In practice, the error data are first identified by frequency components, then the data of each one-dimensional array(in azimuth direction or range direction) are grouped based on numerical distribution period, and finally the error is corrected by the nonlinear model established with each group.This method is verified with measured data from a slope in southern China, and the results show that the method can effectively correct the time-varying baseline error caused by rail instability and effectively improve the monitoring data accuracy of groundbased micro-deformation radar in short term and long term.
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.
基金supported by the National Natural Science Foundation of China(No.62171052 and No.61971054)the Fundamental Research Funds for the Central Universities(No.24820232023YQTD01).
文摘Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.
基金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supported by the Municipal Gavemment of Quzhou(2022D0009,2022D013,2022D033)the Science and Technology Project of Sichuan Province(2023YFG0176)。
文摘There is a growing body of research on the swarm unmanned aerial vehicle(UAV)in recent years,which has the characteristics of small,low speed,and low height as radar target.To confront the swarm UAV,the design of anti-UAV radar system based on multiple input multiple output(MIMO)is put forward,which can elevate the performance of resolution,angle accuracy,high data rate,and tracking flexibility for swarm UAV detection.Target resolution and detection are the core problem in detecting the swarm UAV.The distinct advantage of MIMO system in angular accuracy measurement is demonstrated by comparing MIMO radar with phased array radar.Since MIMO radar has better performance in resolution,swarm UAV detection still has difficulty in target detection.This paper proposes a multi-mode data fusion algorithm based on deep neural networks to improve the detection effect.Subsequently,signal processing and data processing based on the detection fusion algorithm above are designed,forming a high resolution detection loop.Several simulations are designed to illustrate the feasibility of the designed system and the proposed algorithm.
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funded by the National Natural Science Foundation of China,grant number 42074176,U1939204。
文摘Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental perception.However,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(MUSIC)and compressed sensing,etc.,cannot achieve both low complexity and high resolution simultaneously.This paper proposes an efficient 2-D MUSIC algorithm for super-resolution target estimation/tracking based on FMCW radar.Firstly,we enhance the efficiency of 2-D MUSIC azimuth-range spectrum estimation by incorporating 2-D DFT and multi-level resolution searching strategy.Secondly,we apply the gradient descent method to tightly integrate the spatial continuity of object motion into spectrum estimation when processing multi-epoch radar data,which improves the efficiency of continuous target tracking.These two approaches have improved the algorithm efficiency by nearly 2-4 orders of magnitude without losing accuracy and resolution.Simulation experiments are conducted to validate the effectiveness of the algorithm in both single-epoch estimation and multi-epoch tracking scenarios.
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 under Grant 62301119。
文摘The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic reconnaissance.Existing methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative applications.This paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse trains.Simulation results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.