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
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
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
Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic h...Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.展开更多
In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training s...In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial filtering.If the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation effect.To cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range dimension.The principle is presented,and the validity is proven by simulation results.展开更多
In this paper,we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogonal frequency division multiplexing(OFDM)signal.A coarse-fine joint estimation method is proposed to...In this paper,we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogonal frequency division multiplexing(OFDM)signal.A coarse-fine joint estimation method is proposed to achieve better estimation accuracy of target parameters without excessive computational burden.Firstly,the modulation symbol domain(MSD)method is used to roughly estimate the delay and Doppler of targets.Then,to obtain high-precision Doppler estimation,the atomic norm(AN)based on the multiple measurement vectors(MMV)model(MMV-AN)is used to manifest the signal sparsity in the continuous Doppler domain.At the same time,a reference signal compensation(RSC)method is presented to obtain highprecision delay estimation.Simulation results based on the OFDM signal show that the coarse-fine joint estimation method based on AN-RSC can obtain a more accurate estimation of target parameters compared with other algorithms.In addition,the proposed method also possesses computational advantages compared with the joint parameter estimation.展开更多
Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration...Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.展开更多
Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small...Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.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
在自动驾驶场景下的3D目标检测任务中,探索毫米波雷达数据作为RGB图像输入的补充正成为多模态融合的新兴趋势。然而,现有的毫米波雷达-相机融合方法高度依赖于相机的一阶段检测结果,导致整体性能不够理想。本文提供了一种不依赖于相机...在自动驾驶场景下的3D目标检测任务中,探索毫米波雷达数据作为RGB图像输入的补充正成为多模态融合的新兴趋势。然而,现有的毫米波雷达-相机融合方法高度依赖于相机的一阶段检测结果,导致整体性能不够理想。本文提供了一种不依赖于相机检测结果的鸟瞰图下双向融合方法(BEV-radar)。对于来自不同域的两个模态的特征,BEV-radar设计了一个双向的基于注意力的融合策略。具体地,以基于BEV的3D目标检测方法为基础,我们的方法使用双向转换器嵌入来自两种模态的信息,并根据后续的卷积块强制执行局部空间关系。嵌入特征后,BEV特征在3D对象预测头中解码。我们在nu Scenes数据集上评估了我们的方法,实现了48.2 m AP和57.6 NDS。结果显示,与仅使用相机的基础模型相比,不仅在精度上有所提升,特别地,速度预测误差项有了相当大的改进。代码开源于https://github.com/Etah0409/BEV-Radar。展开更多
The jamming resource allocation problem of the aircraft formation cooperatively jamming netted radar system is investigated.An adaptive allocation strategy based on dynamic adaptive discrete cuckoo search algorithm(DA...The jamming resource allocation problem of the aircraft formation cooperatively jamming netted radar system is investigated.An adaptive allocation strategy based on dynamic adaptive discrete cuckoo search algorithm(DADCS)is proposed,whose core is to adjust allocation scheme of limited jamming resource of aircraft formation in real time to maintain the best jamming effectiveness against netted radar system.Firstly,considering the information fusion rules and different working modes of the netted radar system,a two-factor jamming effectiveness evaluation function is constructed,detection probability and aiming probability are adopted to characterize jamming effectiveness against netted radar system in searching and tracking mode,respectively.Then a nonconvex optimization model for cooperatively jamming netted radar system is established.Finally,a dynamic adaptive discrete cuckoo search algorithm(DADCS)is constructed by improving path update strategies and introducing a global learning mechanism,and a three-step solution method is proposed subsequently.Simulation results are provided to demonstrate the advantages of the proposed optimization strategy and the effectiveness of the improved algorithm.展开更多
Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat clima...Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat climate change,sustain soil biodiversity,and regulate water cycling.However,quantifying soil carbon content conventionally is time-consuming,labor-intensive,imprecise,and expensive,making it difficult to accurately measure in-field soil carbon’s effect on storage water and nutrients.To address this challenge,this paper for the first time,reports on extensive lab tests demonstrating non-intrusive methods for sensing soil carbon and related smart biochar applications,such as differentiating between biochar types from various biomass feedstock species,monitoring soil moisture,and biochar water retention capacity using portable microwave and millimeter wave sensors,and machine learning.These methods can be scaled up by deploying the sensor in-field on a mobility platform,either ground or aerial.The paper provides details on the materials,methods,machine learning workflow,and results of our investigations.The significance of this work lays the foundation for assessing carbon-negative technology applications,such as soil carbon content accounting.We validated our quantification method using supervised machine learning algorithms by collecting real soil mixed with known biochar contents in the field.The results show that the millimeter wave sensor achieves high sensing accuracy(up to 100%)with proper classifiers selected and outperforms the microwave sensor by approximately 10%–15%accuracy in sensing soil carbon content.展开更多
During the pre-summer rainy season,heavy rainfall occurs frequently in South China.Based on polarimetric radar observations,the microphysical characteristics and processes of convective features associated with extrem...During the pre-summer rainy season,heavy rainfall occurs frequently in South China.Based on polarimetric radar observations,the microphysical characteristics and processes of convective features associated with extreme rainfall rates(ERCFs)are examined.In the regions with high ERCF occurrence frequency,sub-regional differences are found in the lightning flash rate(LFR)distributions.In the region with higher LFRs,the ERCFs have larger volumes of high reflectivity factor above the freezing level,corresponding to more active riming processes.In addition,these ERCFs are more organized and display larger spatial coverage,which may be related to the stronger low-level wind shear and higher terrain in the region.In the region with lower LFRs,the ERCFs have lower echo tops and lower-echo centroids.However,no clear differences of the most unstable convective available potential energy(MUCAPE)exist in the ERCFs in the regions with different LFR characteristics.Regardless of the LFRs,raindrop collisional coalescence is the main process for the growth of raindrops in the ERCFs.In the ERCFs within the region with lower LFRs,the main mechanism for the rapid increase of liquid water content with decreasing altitude below 4 km is through the warm-rain processes converting cloud drops to raindrops.However,in those with higher LFRs,the liquid water content generally decreases with decreasing altitude.展开更多
Accurate precipitation nowcasting can provide great convenience to the public so they can conduct corresponding arrangements in advance to deal with the possible impact of upcoming heavy rain.Recent relevant research ...Accurate precipitation nowcasting can provide great convenience to the public so they can conduct corresponding arrangements in advance to deal with the possible impact of upcoming heavy rain.Recent relevant research activities have shown their concerns on various deep learning models for radar echo extrapolation,where radar echo maps were used to predict their consequent moment,so as to recognize potential severe convective weather events.However,these approaches suffer from an inaccurate prediction of echo dynamics and unreliable depiction of echo aggregation or dissipation,due to the size limitation of convolution filter,lack of global feature,and less attention to features from previous states.To address the problems,this paper proposes a CEMA-LSTM recurrent unit,which is embedded with a Contextual Feature Correlation Enhancement Block(CEB)and a Multi-Attention Mechanism Block(MAB).The CEB enhances contextual feature correlation and supports its model to memorize significant features for near-future prediction;the MAB uses a position and channel attention mechanism to capture global features of radar echoes.Two practical radar echo datasets were used involving the FREM and CIKM 2017 datasets.Both quantification and visualization of comparative experimental results have demonstrated outperformance of the proposed CEMA-LSTMover recentmodels,e.g.,PhyDNet,MIM and PredRNN++,etc.In particular,compared with the second-rankedmodel,its average POD,FAR and CSI have been improved by 3.87%,1.65%and 1.79%,respectively on the FREM,and by 1.42%,5.60%and 3.16%,respectively on the CIKM 2017.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
In the scene of wideband radar,due to the spread of target scattering points,the attitude and angle of view of the target constantly change in the process of moving.It is difficult to predict,and the actual echo of mu...In the scene of wideband radar,due to the spread of target scattering points,the attitude and angle of view of the target constantly change in the process of moving.It is difficult to predict,and the actual echo of multiple scattered points is not fully matched with the transmitted signal.Therefore,it is challenging for the traditional matching filter method to achieve a complete matching effect in wideband echo detection.In addition,the energy dispersion of complex target echoes is still a problem in radar target detection under broadband conditions.Therefore,this paper proposes a wideband target detection method based on dualchannel correlation processing of range-extended targets.This method fully uses the spatial distribution characteristics of target scattering points of echo signal and the matching characteristics of the dual-channel point extension function itself.The radial accumulation of wideband target echo signal in the complex domain is realized through the adaptive correlation processing of a dual-channel echo signal.The accu-mulation effect of high matching degree is achieved to improve the detection probability and the performance of wideband detection.Finally,electromagnetic simulation experiments and measured data verify that the proposed method has the advan-tages of high signal to noise ratio(SNR)gain and high detection probability under low SNR conditions.展开更多
In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture,this paper conducted soil stratification experiments on agricultural soils...In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture,this paper conducted soil stratification experiments on agricultural soils in the Mollisols area of Northeast China using Ground Penetrating Radar(GPR)and obtained different types of soil with frequencies of 500 MHz,250 MHz,and 100 MHz antennas.The soil profile data were obtained for 500 MHz,250 MHz,and 100 MHz antennas,and the dielectric properties of each type of soil were analyzed.In the image processing procedure,wavelet analysis was first used to decompose the pre-processed radar signal and reconstruct the high-frequency information to obtain the reconstructed signal containing the stratification information.Secondly,the reconstructed signal is taken as an envelope to enhance the stratification information.The Hilbert transform is applied to the envelope signal to find the time-domain variation of the instantaneous frequency and determine the time-domain location of the stratification.Finally,the dielectric constant of each soil horizon is used to obtain the propagation velocity of the electromagnetic wave at the corresponding position to obtain the stratification position of each soil horizon.The research results show that the 500 MHz radar antenna can accurately delineate Ap/Ah,horizon and the absolute accuracy of the stratification is within 5 cm.The effect on the soil stratification below the tillage horizon is not apparent,and the absolute accuracy of the 250 MHz and 100 MHz radar antennas on the stratification is within 9 cm.The overwhelming majority of the overall calculation errors are kept to within 15%.Based on the three central frequency antennas,the soil horizon detection rate reaches 93.3%,which can achieve accurate stratification of soil profiles within 1 m.The experimental and image processing methods used are practical and feasible;however,the GPR will show a missed detection for soil horizons with only slight differences in dielectric properties.Overall,this study can quickly and accurately determine the information of each soil stratification,ultimately providing technical support for acquiring soil configuration information and developing smart agriculture.展开更多
The atmospheric temperatures and densities in the mesosphere and lower thermosphere(MLT)region are essential for studying the dynamics and climate of the middle and upper atmosphere.In this study,we present more than ...The atmospheric temperatures and densities in the mesosphere and lower thermosphere(MLT)region are essential for studying the dynamics and climate of the middle and upper atmosphere.In this study,we present more than 9 years of mesopause temperatures and relative densities estimated by using ambipolar diffusion coefficient measurements observed by the Mengcheng meteor radar(33.4°N,116.5°E).The intercomparison between the meteor radar and Thermosphere Ionosphere Mesosphere Energetics and Dynamics/Sounding of the Atmosphere by Broadband Emission Radiometry(TIMED/SABER)and Earth Observing System(EOS)Aura/Microwave Limb Sounder(MLS)observations indicates that the meteor radar temperatures and densities agree well with the simultaneous satellite measurements.Annual variations dominate the mesopause temperatures,with the maximum during winter and the minimum during summer.The mesopause relative densities also show annual variations,with strong maxima near the spring equinox and weak maxima before the winter solstice,and with a minimum during summer.In addition,the mesopause density exhibits a structure similar to that of the zonal wind:as the zonal wind flows eastward(westward),the mesopause density decreases(increases).At the same time,the meridional wind shows a structure similar to that of the mesopause temperature:as the meridional wind shows northward(southward)enhancements,the mesopause temperature increases(decreases).Simultaneous horizontal wind,temperature,and density observations provide multiple mesospheric parameters for investigating mesospheric dynamics and thermodynamic processes and have the potential to improve widely used empirical atmospheric models.展开更多
By multiplexing information symbols in the delay-Doppler(DD)domain,orthogonal time frequency space(OTFS)is a promising candidate for future wireless communication in high-mobility scenarios.In addition to the superior...By multiplexing information symbols in the delay-Doppler(DD)domain,orthogonal time frequency space(OTFS)is a promising candidate for future wireless communication in high-mobility scenarios.In addition to the superior communication performance,OTFS is also a natural choice for radar sensing since the primary parameters(range and velocity of targets)in radar signal processing can be inferred directly from the delay and Doppler shifts.Though there are several works on OTFS radar sensing,most of them consider the integer parameter estimation only,while the delay and Doppler shifts are usually fractional in the real world.In this paper,we propose a two-step method to estimate the fractional delay and Doppler shifts.We first perform the two-dimensional(2D)correlation between the received and transmitted DD domain symbols to obtain the integer parts of the parameters.Then a difference-based method is implemented to estimate the fractional parts of delay and Doppler indices.Meanwhile,we implement a target detection method based on a generalized likelihood ratio test since the number of potential targets in the sensing scenario is usually unknown.The simulation results show that the proposed method can obtain the delay and Doppler shifts accurately and get the number of sensing targets with a high detection probability.展开更多
The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In t...The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.展开更多
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(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 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the National Natural Science Foundation of China(22265021)the Aeronautical Science Foundation of China(2020Z056056003).
文摘Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.
基金supported by the National Natural Science Foundation of China(62371049)。
文摘In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial filtering.If the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation effect.To cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range dimension.The principle is presented,and the validity is proven by simulation results.
基金supported by the National Natural Science Foundation of China(6193101562071335)+1 种基金the Technological Innovation Project of Hubei Province of China(2019AAA061)the Natural Science F oundation of Hubei Province of China(2021CFA002)。
文摘In this paper,we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogonal frequency division multiplexing(OFDM)signal.A coarse-fine joint estimation method is proposed to achieve better estimation accuracy of target parameters without excessive computational burden.Firstly,the modulation symbol domain(MSD)method is used to roughly estimate the delay and Doppler of targets.Then,to obtain high-precision Doppler estimation,the atomic norm(AN)based on the multiple measurement vectors(MMV)model(MMV-AN)is used to manifest the signal sparsity in the continuous Doppler domain.At the same time,a reference signal compensation(RSC)method is presented to obtain highprecision delay estimation.Simulation results based on the OFDM signal show that the coarse-fine joint estimation method based on AN-RSC can obtain a more accurate estimation of target parameters compared with other algorithms.In addition,the proposed method also possesses computational advantages compared with the joint parameter estimation.
基金supported by the National Natural Science Foundation of China (Nos.51975447,52275268)National Key Research and Development Program of China (No.2021YFC2203600)+2 种基金National Defense Basic Scientific Research Program of China (No.JCKY2021210B007)the Project about Building up“Scientists+Engineers”of Shaanxi Qinchuangyuan Platform (No.2022KXJ-030)Wuhu and Xidian University Special Fund for Industry University Research Cooperation (No.XWYCXY012021-012)。
文摘Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.
文摘Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.
基金supported by the National Natural Science Foundation of China(6177137261771367+3 种基金62101494)the National Outstanding Youth Science Fund Project(61525105)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.
文摘在自动驾驶场景下的3D目标检测任务中,探索毫米波雷达数据作为RGB图像输入的补充正成为多模态融合的新兴趋势。然而,现有的毫米波雷达-相机融合方法高度依赖于相机的一阶段检测结果,导致整体性能不够理想。本文提供了一种不依赖于相机检测结果的鸟瞰图下双向融合方法(BEV-radar)。对于来自不同域的两个模态的特征,BEV-radar设计了一个双向的基于注意力的融合策略。具体地,以基于BEV的3D目标检测方法为基础,我们的方法使用双向转换器嵌入来自两种模态的信息,并根据后续的卷积块强制执行局部空间关系。嵌入特征后,BEV特征在3D对象预测头中解码。我们在nu Scenes数据集上评估了我们的方法,实现了48.2 m AP和57.6 NDS。结果显示,与仅使用相机的基础模型相比,不仅在精度上有所提升,特别地,速度预测误差项有了相当大的改进。代码开源于https://github.com/Etah0409/BEV-Radar。
文摘The jamming resource allocation problem of the aircraft formation cooperatively jamming netted radar system is investigated.An adaptive allocation strategy based on dynamic adaptive discrete cuckoo search algorithm(DADCS)is proposed,whose core is to adjust allocation scheme of limited jamming resource of aircraft formation in real time to maintain the best jamming effectiveness against netted radar system.Firstly,considering the information fusion rules and different working modes of the netted radar system,a two-factor jamming effectiveness evaluation function is constructed,detection probability and aiming probability are adopted to characterize jamming effectiveness against netted radar system in searching and tracking mode,respectively.Then a nonconvex optimization model for cooperatively jamming netted radar system is established.Finally,a dynamic adaptive discrete cuckoo search algorithm(DADCS)is constructed by improving path update strategies and introducing a global learning mechanism,and a three-step solution method is proposed subsequently.Simulation results are provided to demonstrate the advantages of the proposed optimization strategy and the effectiveness of the improved algorithm.
基金supported by SGC project5 entitled"Mobile Biochar Production for Methane Emission Reduction and Soil Amendment".Grant Agreement#CCR20014supported in part by NSF CBET#1856112supported in part by an F3 R&D GSR Award (Farms Food Future Innovation Initiative (or F3),as funded by US Dept.of Commerce,Economic Development Administration Build Back Better Regional Challenge).
文摘Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat climate change,sustain soil biodiversity,and regulate water cycling.However,quantifying soil carbon content conventionally is time-consuming,labor-intensive,imprecise,and expensive,making it difficult to accurately measure in-field soil carbon’s effect on storage water and nutrients.To address this challenge,this paper for the first time,reports on extensive lab tests demonstrating non-intrusive methods for sensing soil carbon and related smart biochar applications,such as differentiating between biochar types from various biomass feedstock species,monitoring soil moisture,and biochar water retention capacity using portable microwave and millimeter wave sensors,and machine learning.These methods can be scaled up by deploying the sensor in-field on a mobility platform,either ground or aerial.The paper provides details on the materials,methods,machine learning workflow,and results of our investigations.The significance of this work lays the foundation for assessing carbon-negative technology applications,such as soil carbon content accounting.We validated our quantification method using supervised machine learning algorithms by collecting real soil mixed with known biochar contents in the field.The results show that the millimeter wave sensor achieves high sensing accuracy(up to 100%)with proper classifiers selected and outperforms the microwave sensor by approximately 10%–15%accuracy in sensing soil carbon content.
基金primarily supported by the National Natural Science Foundation of China(Grant Nos.42025501,41905019,and 61827901)the National Key Research and Development Program of China(Grant 2018YFC1506404 and Grant 2017YFC1501703)。
文摘During the pre-summer rainy season,heavy rainfall occurs frequently in South China.Based on polarimetric radar observations,the microphysical characteristics and processes of convective features associated with extreme rainfall rates(ERCFs)are examined.In the regions with high ERCF occurrence frequency,sub-regional differences are found in the lightning flash rate(LFR)distributions.In the region with higher LFRs,the ERCFs have larger volumes of high reflectivity factor above the freezing level,corresponding to more active riming processes.In addition,these ERCFs are more organized and display larger spatial coverage,which may be related to the stronger low-level wind shear and higher terrain in the region.In the region with lower LFRs,the ERCFs have lower echo tops and lower-echo centroids.However,no clear differences of the most unstable convective available potential energy(MUCAPE)exist in the ERCFs in the regions with different LFR characteristics.Regardless of the LFRs,raindrop collisional coalescence is the main process for the growth of raindrops in the ERCFs.In the ERCFs within the region with lower LFRs,the main mechanism for the rapid increase of liquid water content with decreasing altitude below 4 km is through the warm-rain processes converting cloud drops to raindrops.However,in those with higher LFRs,the liquid water content generally decreases with decreasing altitude.
基金funding from the Key Laboratory Foundation of National Defence Technology under Grant 61424010208National Natural Science Foundation of China(Nos.62002276,41911530242 and 41975142)+3 种基金5150 Spring Specialists(05492018012 and 05762018039)Major Program of the National Social Science Fund of China(Grant No.17ZDA092)333 High-LevelTalent Cultivation Project of Jiangsu Province(BRA2018332)Royal Society of Edinburgh,UK andChina Natural Science Foundation Council(RSE Reference:62967)_Liu)_2018)_2)under their Joint International Projects Funding Scheme and Basic Research Programs(Natural Science Foundation)of Jiangsu Province(BK20191398 and BK20180794).
文摘Accurate precipitation nowcasting can provide great convenience to the public so they can conduct corresponding arrangements in advance to deal with the possible impact of upcoming heavy rain.Recent relevant research activities have shown their concerns on various deep learning models for radar echo extrapolation,where radar echo maps were used to predict their consequent moment,so as to recognize potential severe convective weather events.However,these approaches suffer from an inaccurate prediction of echo dynamics and unreliable depiction of echo aggregation or dissipation,due to the size limitation of convolution filter,lack of global feature,and less attention to features from previous states.To address the problems,this paper proposes a CEMA-LSTM recurrent unit,which is embedded with a Contextual Feature Correlation Enhancement Block(CEB)and a Multi-Attention Mechanism Block(MAB).The CEB enhances contextual feature correlation and supports its model to memorize significant features for near-future prediction;the MAB uses a position and channel attention mechanism to capture global features of radar echoes.Two practical radar echo datasets were used involving the FREM and CIKM 2017 datasets.Both quantification and visualization of comparative experimental results have demonstrated outperformance of the proposed CEMA-LSTMover recentmodels,e.g.,PhyDNet,MIM and PredRNN++,etc.In particular,compared with the second-rankedmodel,its average POD,FAR and CSI have been improved by 3.87%,1.65%and 1.79%,respectively on the FREM,and by 1.42%,5.60%and 3.16%,respectively on the CIKM 2017.
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.
文摘In the scene of wideband radar,due to the spread of target scattering points,the attitude and angle of view of the target constantly change in the process of moving.It is difficult to predict,and the actual echo of multiple scattered points is not fully matched with the transmitted signal.Therefore,it is challenging for the traditional matching filter method to achieve a complete matching effect in wideband echo detection.In addition,the energy dispersion of complex target echoes is still a problem in radar target detection under broadband conditions.Therefore,this paper proposes a wideband target detection method based on dualchannel correlation processing of range-extended targets.This method fully uses the spatial distribution characteristics of target scattering points of echo signal and the matching characteristics of the dual-channel point extension function itself.The radial accumulation of wideband target echo signal in the complex domain is realized through the adaptive correlation processing of a dual-channel echo signal.The accu-mulation effect of high matching degree is achieved to improve the detection probability and the performance of wideband detection.Finally,electromagnetic simulation experiments and measured data verify that the proposed method has the advan-tages of high signal to noise ratio(SNR)gain and high detection probability under low SNR conditions.
基金Under the auspices of the National Key R&D Program of China(No.2021YFD1500100)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA28100000)。
文摘In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture,this paper conducted soil stratification experiments on agricultural soils in the Mollisols area of Northeast China using Ground Penetrating Radar(GPR)and obtained different types of soil with frequencies of 500 MHz,250 MHz,and 100 MHz antennas.The soil profile data were obtained for 500 MHz,250 MHz,and 100 MHz antennas,and the dielectric properties of each type of soil were analyzed.In the image processing procedure,wavelet analysis was first used to decompose the pre-processed radar signal and reconstruct the high-frequency information to obtain the reconstructed signal containing the stratification information.Secondly,the reconstructed signal is taken as an envelope to enhance the stratification information.The Hilbert transform is applied to the envelope signal to find the time-domain variation of the instantaneous frequency and determine the time-domain location of the stratification.Finally,the dielectric constant of each soil horizon is used to obtain the propagation velocity of the electromagnetic wave at the corresponding position to obtain the stratification position of each soil horizon.The research results show that the 500 MHz radar antenna can accurately delineate Ap/Ah,horizon and the absolute accuracy of the stratification is within 5 cm.The effect on the soil stratification below the tillage horizon is not apparent,and the absolute accuracy of the 250 MHz and 100 MHz radar antennas on the stratification is within 9 cm.The overwhelming majority of the overall calculation errors are kept to within 15%.Based on the three central frequency antennas,the soil horizon detection rate reaches 93.3%,which can achieve accurate stratification of soil profiles within 1 m.The experimental and image processing methods used are practical and feasible;however,the GPR will show a missed detection for soil horizons with only slight differences in dielectric properties.Overall,this study can quickly and accurately determine the information of each soil stratification,ultimately providing technical support for acquiring soil configuration information and developing smart agriculture.
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)+5 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 Environmentthe Fundamental Research Funds for the Central Universitiesthe Chinese Meridian Projectfunded by the Anhui Provincial Natural Science Foundation (Grant No. 2008085MD113)the Joint Open Fund of Mengcheng National Geophysical Observatory (No. MENGO-202209)
文摘The atmospheric temperatures and densities in the mesosphere and lower thermosphere(MLT)region are essential for studying the dynamics and climate of the middle and upper atmosphere.In this study,we present more than 9 years of mesopause temperatures and relative densities estimated by using ambipolar diffusion coefficient measurements observed by the Mengcheng meteor radar(33.4°N,116.5°E).The intercomparison between the meteor radar and Thermosphere Ionosphere Mesosphere Energetics and Dynamics/Sounding of the Atmosphere by Broadband Emission Radiometry(TIMED/SABER)and Earth Observing System(EOS)Aura/Microwave Limb Sounder(MLS)observations indicates that the meteor radar temperatures and densities agree well with the simultaneous satellite measurements.Annual variations dominate the mesopause temperatures,with the maximum during winter and the minimum during summer.The mesopause relative densities also show annual variations,with strong maxima near the spring equinox and weak maxima before the winter solstice,and with a minimum during summer.In addition,the mesopause density exhibits a structure similar to that of the zonal wind:as the zonal wind flows eastward(westward),the mesopause density decreases(increases).At the same time,the meridional wind shows a structure similar to that of the mesopause temperature:as the meridional wind shows northward(southward)enhancements,the mesopause temperature increases(decreases).Simultaneous horizontal wind,temperature,and density observations provide multiple mesospheric parameters for investigating mesospheric dynamics and thermodynamic processes and have the potential to improve widely used empirical atmospheric models.
文摘By multiplexing information symbols in the delay-Doppler(DD)domain,orthogonal time frequency space(OTFS)is a promising candidate for future wireless communication in high-mobility scenarios.In addition to the superior communication performance,OTFS is also a natural choice for radar sensing since the primary parameters(range and velocity of targets)in radar signal processing can be inferred directly from the delay and Doppler shifts.Though there are several works on OTFS radar sensing,most of them consider the integer parameter estimation only,while the delay and Doppler shifts are usually fractional in the real world.In this paper,we propose a two-step method to estimate the fractional delay and Doppler shifts.We first perform the two-dimensional(2D)correlation between the received and transmitted DD domain symbols to obtain the integer parts of the parameters.Then a difference-based method is implemented to estimate the fractional parts of delay and Doppler indices.Meanwhile,we implement a target detection method based on a generalized likelihood ratio test since the number of potential targets in the sensing scenario is usually unknown.The simulation results show that the proposed method can obtain the delay and Doppler shifts accurately and get the number of sensing targets with a high detection probability.
基金National Natural Science Foundation of China(Grant No.62001506)to provide fund for conducting experiments。
文摘The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.
