Waveform regulator in charge is a method that can realize multi-source detonation wave superposition through a single point detonation.The method does not need to weaken the strength of shell,and relies on the high st...Waveform regulator in charge is a method that can realize multi-source detonation wave superposition through a single point detonation.The method does not need to weaken the strength of shell,and relies on the high stress generated by superposition to cut shell into regular fragments.Additionally,it can be combined with different initiation methods to alter the fragmentation outcomes.In this study,aiming at the fracture strain of metal cylindrical shell driven by explosive charge with waveform regulator,theoretical analysis was first adopted to obtain the prediction model of the fracture strain of cylindrical shell with waveform regulator and the model of the axial distribution of the stress concentration factor.On this basis,both theoretical analysis and numerical models were utilized to investigate the effect of waveform regulator on the initial velocity of fragments.Finally,experiments were conducted to validate the fracture strain prediction model for cylindrical shell with waveform regulator.The research results show that the collision angles of the detonation waves at different axial positions are different,which leads to the stress concentration factor on the shell presenting a trend of gradually decreasing,then sharply increasing,and then rapidly decreasing along the axial direction.Additionally,the changes in the slot spacing and the thickness of outer charge will also affect the stress concentration factor,and the influence of outer charge thickness is relatively large.The smaller the ratio of charge volume to waveform regulator volume,the larger the axial sparse wave intensity and the more the fragment initial velocity decrease.From the initiation end to the non-initiation end,the failure modes of the shell sequentially change from pure shear,to mixed tensile-shear,and finally to pure tensile failure.The experimental results are in good agreement with the calculated results of the fracture strain model,and the maximum relative error is less than 10%,which indicates that the fracture strain prediction model of the cylindrical shell with waveform regulator established in this paper by considering the increase of elastic energy per unit volume caused by stress concentration on the shell is reliable.展开更多
Low sidelobe waveform can reduce mutual masking between targets and increase the detection probability of weak targets.A low sidelobe waveform design method based on complementary amplitude coding(CAC)is proposed in t...Low sidelobe waveform can reduce mutual masking between targets and increase the detection probability of weak targets.A low sidelobe waveform design method based on complementary amplitude coding(CAC)is proposed in this paper,which can be used to reduce the sidelobe level of multiple waveforms.First,the CAC model is constructed.Then,the waveform design problem is transformed into a nonlinear optimization problem by constructing an objective function using the two indicators of peak-to-sidelobe ratio(PSLR)and integrated sidelobe ratio(ISLR).Finally,genetic algorithm(GA)is used to solve the optimization problem to get the best CAC waveforms.Simulations and experiments are conducted to verify the effectiveness of the proposed method.展开更多
Orthogonal waveform design is quite an important issue for waveform diversity systems. A chaos based method for the orthogonal discrete frequency coding waveform （DFCW） design is proposed to increase the insufficien...Orthogonal waveform design is quite an important issue for waveform diversity systems. A chaos based method for the orthogonal discrete frequency coding waveform （DFCW） design is proposed to increase the insufficient orthogonal waveform number and their finite coding length. Premises for chaos choosing and the frequency quantification method are discussed to obtain the best correlation properties. Simulation results show the validity of the theoretic analysis.展开更多
We assembled approximately 328 seismic records. The data set was from 4 digitally recording long-period and broadband stations of CDSN. We carried out the inversion based on the partitioned waveform inversion (PWI). I...We assembled approximately 328 seismic records. The data set was from 4 digitally recording long-period and broadband stations of CDSN. We carried out the inversion based on the partitioned waveform inversion (PWI). It partitions the large-scale optimization problem into a number of independent small-scale problems. We adopted surface waveform inversion with an equal block (2((2() discretization in order to acquire the images of shear velocity structure at different depths (from surface to 430 km) in the crust and upper-mantle. The resolution of all these anomalies has been established with (check-board( resolution tests. These results show significant difference in velocity, lithosphere and asthenosphere structure between South China Sea and its adjacent regions.展开更多
Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic ev...Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic events for providing accurate information of rockmass.The accurate identification of microseismic events and blasts determines the timeliness and accuracy of early warning of microseismic monitoring technology.An image identification model based on Convolutional Neural Network(CNN)is established in this paper for the seismic waveforms of microseismic events and blasts.Firstly,the training set,test set,and validation set are collected,which are composed of 5250,1500,and 750 seismic waveforms of microseismic events and blasts,respectively.The classified data sets are preprocessed and input into the constructed CNN in CPU mode for training.Results show that the accuracies of microseismic events and blasts are 99.46%and 99.33%in the test set,respectively.The accuracies of microseismic events and blasts are 100%and 98.13%in the validation set,respectively.The proposed method gives superior performance when compared with existed methods.The accuracies of models using logistic regression and artificial neural network(ANN)based on the same data set are 54.43%and 67.9%in the test set,respectively.Then,the ROC curves of the three models are obtained and compared,which show that the CNN gives an absolute advantage in this classification model when the original seismic waveform are used in training the model.It not only decreases the influence of individual differences in experience,but also removes the errors induced by source and waveform parameters.It is proved that the established discriminant method improves the efficiency and accuracy of microseismic data processing for monitoring rock instability and seismicity.展开更多
Acoustic Emission(AE)waveforms contain information on microscopic structural features that can be related with damage of coal rock masses.In this paper,the Hilbert-Huang transform(HHT)method is used to obtain detailed...Acoustic Emission(AE)waveforms contain information on microscopic structural features that can be related with damage of coal rock masses.In this paper,the Hilbert-Huang transform(HHT)method is used to obtain detailed structural characteristics of coal rock masses associated with damage,at different loading stages,from the analyses of the characteristics of AE waveforms.The results show that the HHT method can be used to decompose the target waveform into multiple intrinsic mode function(IMF)components,with the energy mainly concentrated in the c1−c4 IMF components,where the c1 component has the highest frequency and the largest amount of energy.As the loading continues,the proportion of energy occupied by the low-frequency IMF component shows an increasing trend.In the initial compaction stage,the Hilbert marginal spectrum is mainly concentrated in the low frequency range of 0−40 kHz.The plastic deformation stage is associated to energy accumulation in the frequency range of 0−25 kHz and 200−350 kHz,while the instability damage stage is mainly concentrated in the frequency range of 0−25 kHz.At 20 kHz,the instability damage reaches its maximum value.There is a relatively clear instantaneous energy peak at each stage,albeit being more distinct at the beginning and at the end of the compaction phase.Since the effective duration of the waveform is short,its resulting energy is small,and so there is a relatively high value from the instantaneous energy peak.The waveform lasts a relatively long time after the peak that coincides with failure,which is the period where the waveform reaches its maximum energy level.The Hilbert three-dimensional energy spectrum is generally zero in the region where the real energy is zero.In addition,its energy spectrum is intermittent rather than continuous.It is therefore consistent with the characteristics of the several dynamic ranges mentioned above,and it indicates more clearly the low-frequency energy concentration in the critical stage of instability failure.This study well reflects the response law of geophysical signals in the process of coal rock instability and failure,providing a basis for monitoring coal rock dynamic disasters.展开更多
Transmit waveform optimization is critical to radar system performance. There have been a fruit of achievements about waveform design in recent years. However, most of the existing methods are based on the assumption ...Transmit waveform optimization is critical to radar system performance. There have been a fruit of achievements about waveform design in recent years. However, most of the existing methods are based on the assumption that radar is smart and the target is dumb, which is not always reasonable in the modern electronic warfare. This paper focuses on the waveform design for radar and the extended target in the environment of electronic warfare. Three different countermeasure models between smart radar and dumb target, smart target and dumb radar, smart radar and smart target are proposed. Taking the signal-to-interferenceplus-noise ratio(SINR) as the metric, optimized waveforms for the first two scenarios are achieved by the general water-filling method in the presence of clutter. For the last case, the equilibrium between smart radar and smart target in the presence of clutter is given mathematically and the optimized solution is achieved through a novel two-step water-filling method on the basis of minmax theory. Simulation results under different power constraints show the power allocation strategies of radar and target and the output SINRs are analyzed.展开更多
The principle and method of both radar target imaging and velocity measurement simultaneously based on step frequency waveforms is presented. Velocity compensation is necessary in order to obtain the good High resolut...The principle and method of both radar target imaging and velocity measurement simultaneously based on step frequency waveforms is presented. Velocity compensation is necessary in order to obtain the good High resolution range profile since this waveform is greatly sensitive to the Doppler shift. The velocity measurement performance of the four styles is analyzed with two pulse trains consisted of positive and negative step frequency waveforms. The velocity of targets can be estimated first coarsely by using the pulse trains with positive-positive step frequency combination, and then fine by positive-negative combination. Simulation results indicate that the method can accomplish the accurate estimation of the velocity with efficient computation and good anti-noise performance and obtain the good HRRP simultaneously.展开更多
The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The tr...The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.展开更多
The particle simulation method is used to study the effects of loading waveforms （i.e. square, sinusoidal and triangle waveforms） on rock damage at mesoscopic scale. Then some influencing factors on rock damage at t...The particle simulation method is used to study the effects of loading waveforms （i.e. square, sinusoidal and triangle waveforms） on rock damage at mesoscopic scale. Then some influencing factors on rock damage at the mesoscopic scale, such as loading frequency, stress amplitude, mean stress, confining pressure and loading sequence, are also investigated with sinusoidal waveform in detail. The related numerical results have demonstrated that： 1） the loading waveform has a certain effect on rock failure processes. The square waveform has the most damage within these waveforms, while the triangle waveform has less damage than sinusoidal waveform. In each cycle, the number of microscopic cracks increases in the loading stage, while it keeps nearly constant in the unloading stage. 2） The loading frequency, stress amplitude, mean stress, confining pressure and loading sequence have considerable effects on rock damage subjected to cyclic loading. The higher the loading frequency, stress amplitude and mean stress, the greater the damage the rock accumulated; in contrast, the lower the confining pressure, the greater the damage the rock has accumulated. 3） There is a threshold value of mean stress and stress amplitude, below which no further damage accumulated after the first few cycle loadings. 4） The high-to-low loading sequence has more damage than the low-to-high loading sequence, suggesting that the rock damage is loading-path dependent.展开更多
Collocated multiple input multiple output(MIMO)radar,which has agile multi-beam working mode,can offer enhanced multiple targets tracking(MTT)ability.In detail,it can illuminate different targets simultaneously with m...Collocated multiple input multiple output(MIMO)radar,which has agile multi-beam working mode,can offer enhanced multiple targets tracking(MTT)ability.In detail,it can illuminate different targets simultaneously with multi-beam or one wide beam among multi-beam,providing greater degree of freedom in system resource control.An adaptive time-space resource and waveform control optimization model for the collocated MIMO radar with simultaneous multi-beam is proposed in this paper.The aim of the proposed scheme is to improve the overall tracking accuracy and meanwhile minimize the resource consumption under the guarantee of effective targets detection.A resource and waveform control algorithm which integrates the genetic algorithm(GA)is proposed to solve the optimization problem.The optimal transmitting waveform parameters,system sampling period,sub-array number,binary radar tracking parameterχ_i(t_k),transmitting energy and multi-beam direction vector combination are chosen adaptively,where the first one realizes the waveform control and the latter five realize the timespace resource allocation.Simulation results demonstrate the effectiveness of the proposed control method.展开更多
Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fix...Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fixed threshold voltage value for gray scale display.In addition,the display has to repeatedly refresh between white and black states to eliminate ghost image when it needs to update a new image.The traditional driving waveform for the EPD includes four stages: erasing the original image,resetting to black state,clearing to white state,and writing a new image.A flicker can be found when transferring between two adjacent stages.A new driving waveform based on the improvement of activation pattern is proposed to weaken the ghost image and reduce the flicker.Experimental results show that the proposed driving waveform could weaken the ghost image effectively and reduce the number of flickers by 50%.Compared with the traditional driving waveform,the driving waveform of this work has a better performance.展开更多
The problems of joint adaptive waveform design and baseline range design for bistatic radar to maximize the practical radar resolution were considered.Distinguishing from the conventional ambiguity function(AF)-based ...The problems of joint adaptive waveform design and baseline range design for bistatic radar to maximize the practical radar resolution were considered.Distinguishing from the conventional ambiguity function(AF)-based resolution which is only related with the transmitted waveform and bistatic geometry and could be regarded as the potential resolution of a bistatic radar system,the practical resolution involves the effect of waveform,signal-to-noise ratio(SNR)as well as the measurement model.Thus,it is more practical and will have further significant application in target detection and tracking.The constraint optimization procedure of joint adaptive waveform design and baseline range design for maximizing the practical resolution of bistatic radar system under dynamic target scenario was devised.Simulation results show that the range and velocity resolution are enhanced according to the adaptive waveform and bistatic radar configuration.展开更多
Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributio...Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.展开更多
In this paper,218 long period Rayleigh wave records from 7 seismic station of CDSN are selected.We applied a partitioned waveform inversion to these data in order to construct a 3\|D model of shear velocity down to 40...In this paper,218 long period Rayleigh wave records from 7 seismic station of CDSN are selected.We applied a partitioned waveform inversion to these data in order to construct a 3\|D model of shear velocity down to 400km depth in the crust and upper mantle of Qinghai\|Tibet plateau and Its Adjacent Regions (22°～44°N,70°～110°E).The first step of the waveform inversion used involved the matching of the waveforms of fundamental and highermost Ravleigh waves with waveforms synthesized from stratified models;in the second stage,the 3\|D model was constructed by solve linear constrains equation. The major structural features inferred from the surface waveform inversions can be summarized as follows:(1) There is a great contrast between surface waveform through Qinghai—Thibet plateau and the others.Main frequency of the former is lower than the latter, which indicate the crust depth of Qinghai—Tibet plateau is deeper than the others. In addition,the amplitude of about 30s period and 50s period is lower than both sides,which implied these exist lower velocity layer at about 25km depth and about 50km depth in Qinghai—Tibet plateau Crust.The former is common,the latter was argued because resolution of most method can not prove it.展开更多
With the continuous improvement of radar intelligence, it is difficult for traditional countermeasures to achieve ideal results. In order to deal with complex, changeable, and unknown threat signals in the complex ele...With the continuous improvement of radar intelligence, it is difficult for traditional countermeasures to achieve ideal results. In order to deal with complex, changeable, and unknown threat signals in the complex electromagnetic environment, a waveform intelligent optimization model based on intelligent optimization algorithm is proposed. By virtue of the universality and fast running speed of the intelligent optimization algorithm, the model can optimize the parameters used to synthesize the countermeasure waveform according to different external signals, so as to improve the countermeasure performance.Genetic algorithm(GA) and particle swarm optimization(PSO)are used to simulate the intelligent optimization of interruptedsampling and phase-modulation repeater waveform. The experimental results under different radar signal conditions show that the scheme is feasible. The performance comparison between the algorithms and some problems in the experimental results also provide a certain reference for the follow-up work.展开更多
In this paper, we propose a joint waveform selection and power allocation(JWSPA) strategy based on chance-constraint programming(CCP) for manned/unmanned aerial vehicle hybrid swarm(M/UAVHS) tracking a single target. ...In this paper, we propose a joint waveform selection and power allocation(JWSPA) strategy based on chance-constraint programming(CCP) for manned/unmanned aerial vehicle hybrid swarm(M/UAVHS) tracking a single target. Accordingly,the low probability of intercept(LPI) performance of system can be improved by collaboratively optimizing transmit power and waveform. For target radar cross section(RCS) prediction, we design a random RCS prediction model based on electromagnetic simulation(ES) of target. For waveform selection, we build a waveform library to adaptively manage the frequency modulation slope and pulse width of radar waveform. For power allocation,the CCP is employed to balance tracking accuracy and power resource. The Bayesian Cramér-Rao lower bound(BCRLB) is adopted as a criterion to measure target tracking accuracy. The hybrid intelli gent algorithms, in which the stochastic simulation is integrated into the genetic algorithm(GA), are used to solve the stochastic optimization problem. Simulation results demonstrate that the proposed JWSPA strategy can save more transmit power than the traditional fixed waveform scheme under the same target tracking accuracy.展开更多
For the issue of deterioration in detection performance caused by dynamically changing environment in ultra-wideband（UWB） multiple input multiple output（MIMO） radar, this paper proposes a novel adaptive waveform d...For the issue of deterioration in detection performance caused by dynamically changing environment in ultra-wideband（UWB） multiple input multiple output（MIMO） radar, this paper proposes a novel adaptive waveform design which is aimed to improve the ability of discriminating target and clutter from the radar scene. Firstly, a sequence of Morlet wavelet pulses with frequency hopping and pulse position modulation by Welch-Costas array is designed. Then a waveform optimization solution is proposed which is achieved by applying the minimization mutual-information（MI） strategy. After that, with subsequent iterations of the algorithm, simulation results demonstrate that the optimal waveform design method brings an improvement in the target detection ability in the presence of noise and clutter.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.12302437)Natural Science Foundation of Jiangsu Province(Grant No.SBK2023045424)。
文摘Waveform regulator in charge is a method that can realize multi-source detonation wave superposition through a single point detonation.The method does not need to weaken the strength of shell,and relies on the high stress generated by superposition to cut shell into regular fragments.Additionally,it can be combined with different initiation methods to alter the fragmentation outcomes.In this study,aiming at the fracture strain of metal cylindrical shell driven by explosive charge with waveform regulator,theoretical analysis was first adopted to obtain the prediction model of the fracture strain of cylindrical shell with waveform regulator and the model of the axial distribution of the stress concentration factor.On this basis,both theoretical analysis and numerical models were utilized to investigate the effect of waveform regulator on the initial velocity of fragments.Finally,experiments were conducted to validate the fracture strain prediction model for cylindrical shell with waveform regulator.The research results show that the collision angles of the detonation waves at different axial positions are different,which leads to the stress concentration factor on the shell presenting a trend of gradually decreasing,then sharply increasing,and then rapidly decreasing along the axial direction.Additionally,the changes in the slot spacing and the thickness of outer charge will also affect the stress concentration factor,and the influence of outer charge thickness is relatively large.The smaller the ratio of charge volume to waveform regulator volume,the larger the axial sparse wave intensity and the more the fragment initial velocity decrease.From the initiation end to the non-initiation end,the failure modes of the shell sequentially change from pure shear,to mixed tensile-shear,and finally to pure tensile failure.The experimental results are in good agreement with the calculated results of the fracture strain model,and the maximum relative error is less than 10%,which indicates that the fracture strain prediction model of the cylindrical shell with waveform regulator established in this paper by considering the increase of elastic energy per unit volume caused by stress concentration on the shell is reliable.
基金supported by the National Natural Science Foundation of China(62001481,61890542)the Natural Science Foundation of Hunan Province(2021JJ40686).
文摘Low sidelobe waveform can reduce mutual masking between targets and increase the detection probability of weak targets.A low sidelobe waveform design method based on complementary amplitude coding(CAC)is proposed in this paper,which can be used to reduce the sidelobe level of multiple waveforms.First,the CAC model is constructed.Then,the waveform design problem is transformed into a nonlinear optimization problem by constructing an objective function using the two indicators of peak-to-sidelobe ratio(PSLR)and integrated sidelobe ratio(ISLR).Finally,genetic algorithm(GA)is used to solve the optimization problem to get the best CAC waveforms.Simulations and experiments are conducted to verify the effectiveness of the proposed method.
基金supported by the Hunan Province Distinguished Ph.D. Innovation Fund (CX2012B018)the National University of Defense Technology Distinguished Ph.D. Innovation Fund (B120403)
文摘Orthogonal waveform design is quite an important issue for waveform diversity systems. A chaos based method for the orthogonal discrete frequency coding waveform （DFCW） design is proposed to increase the insufficient orthogonal waveform number and their finite coding length. Premises for chaos choosing and the frequency quantification method are discussed to obtain the best correlation properties. Simulation results show the validity of the theoretic analysis.
基金State Natural Scientific Foundation (49734150) and National High Performance Computation Foundation.
文摘We assembled approximately 328 seismic records. The data set was from 4 digitally recording long-period and broadband stations of CDSN. We carried out the inversion based on the partitioned waveform inversion (PWI). It partitions the large-scale optimization problem into a number of independent small-scale problems. We adopted surface waveform inversion with an equal block (2((2() discretization in order to acquire the images of shear velocity structure at different depths (from surface to 430 km) in the crust and upper-mantle. The resolution of all these anomalies has been established with (check-board( resolution tests. These results show significant difference in velocity, lithosphere and asthenosphere structure between South China Sea and its adjacent regions.
基金Projects(51822407,51774327,51664016)supported by the National Natural Science Foundation of China。
文摘Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic events for providing accurate information of rockmass.The accurate identification of microseismic events and blasts determines the timeliness and accuracy of early warning of microseismic monitoring technology.An image identification model based on Convolutional Neural Network(CNN)is established in this paper for the seismic waveforms of microseismic events and blasts.Firstly,the training set,test set,and validation set are collected,which are composed of 5250,1500,and 750 seismic waveforms of microseismic events and blasts,respectively.The classified data sets are preprocessed and input into the constructed CNN in CPU mode for training.Results show that the accuracies of microseismic events and blasts are 99.46%and 99.33%in the test set,respectively.The accuracies of microseismic events and blasts are 100%and 98.13%in the validation set,respectively.The proposed method gives superior performance when compared with existed methods.The accuracies of models using logistic regression and artificial neural network(ANN)based on the same data set are 54.43%and 67.9%in the test set,respectively.Then,the ROC curves of the three models are obtained and compared,which show that the CNN gives an absolute advantage in this classification model when the original seismic waveform are used in training the model.It not only decreases the influence of individual differences in experience,but also removes the errors induced by source and waveform parameters.It is proved that the established discriminant method improves the efficiency and accuracy of microseismic data processing for monitoring rock instability and seismicity.
基金Projects(51904167, 51474134, 51774194) supported by the National Natural Science Foundation of ChinaProject(SKLCRSM19KF008) supported by the Research Fund of the State Key Laboratory of Coal Resources and Safe Mining,CUMT,China+5 种基金Project(cstc2019jcyj-bsh0041) supported by the Natural Science Foundation of Chongqing,ChinaProject(2011DA105287-BH201903) supported by the Postdoctoral ScienceFunded by State Key Laboratory of Coal Mine Disaster Dynamics and Control,ChinaProject(2019SDZY034-2) supported by the Key R&D plan of Shandong Province,ChinaProject(2020M670781) supported by the China Postdoctoral Science FoundationProject supported by the Taishan Scholars ProjectProject supported by the Taishan Scholar Talent Team Support Plan for Advantaged&Unique Discipline Areas,China
文摘Acoustic Emission(AE)waveforms contain information on microscopic structural features that can be related with damage of coal rock masses.In this paper,the Hilbert-Huang transform(HHT)method is used to obtain detailed structural characteristics of coal rock masses associated with damage,at different loading stages,from the analyses of the characteristics of AE waveforms.The results show that the HHT method can be used to decompose the target waveform into multiple intrinsic mode function(IMF)components,with the energy mainly concentrated in the c1−c4 IMF components,where the c1 component has the highest frequency and the largest amount of energy.As the loading continues,the proportion of energy occupied by the low-frequency IMF component shows an increasing trend.In the initial compaction stage,the Hilbert marginal spectrum is mainly concentrated in the low frequency range of 0−40 kHz.The plastic deformation stage is associated to energy accumulation in the frequency range of 0−25 kHz and 200−350 kHz,while the instability damage stage is mainly concentrated in the frequency range of 0−25 kHz.At 20 kHz,the instability damage reaches its maximum value.There is a relatively clear instantaneous energy peak at each stage,albeit being more distinct at the beginning and at the end of the compaction phase.Since the effective duration of the waveform is short,its resulting energy is small,and so there is a relatively high value from the instantaneous energy peak.The waveform lasts a relatively long time after the peak that coincides with failure,which is the period where the waveform reaches its maximum energy level.The Hilbert three-dimensional energy spectrum is generally zero in the region where the real energy is zero.In addition,its energy spectrum is intermittent rather than continuous.It is therefore consistent with the characteristics of the several dynamic ranges mentioned above,and it indicates more clearly the low-frequency energy concentration in the critical stage of instability failure.This study well reflects the response law of geophysical signals in the process of coal rock instability and failure,providing a basis for monitoring coal rock dynamic disasters.
基金supported by the National Natural Science Foundation of China(61302153)the Aeronautical Science Foundation of China(20160196001)
文摘Transmit waveform optimization is critical to radar system performance. There have been a fruit of achievements about waveform design in recent years. However, most of the existing methods are based on the assumption that radar is smart and the target is dumb, which is not always reasonable in the modern electronic warfare. This paper focuses on the waveform design for radar and the extended target in the environment of electronic warfare. Three different countermeasure models between smart radar and dumb target, smart target and dumb radar, smart radar and smart target are proposed. Taking the signal-to-interferenceplus-noise ratio(SINR) as the metric, optimized waveforms for the first two scenarios are achieved by the general water-filling method in the presence of clutter. For the last case, the equilibrium between smart radar and smart target in the presence of clutter is given mathematically and the optimized solution is achieved through a novel two-step water-filling method on the basis of minmax theory. Simulation results under different power constraints show the power allocation strategies of radar and target and the output SINRs are analyzed.
文摘The principle and method of both radar target imaging and velocity measurement simultaneously based on step frequency waveforms is presented. Velocity compensation is necessary in order to obtain the good High resolution range profile since this waveform is greatly sensitive to the Doppler shift. The velocity measurement performance of the four styles is analyzed with two pulse trains consisted of positive and negative step frequency waveforms. The velocity of targets can be estimated first coarsely by using the pulse trains with positive-positive step frequency combination, and then fine by positive-negative combination. Simulation results indicate that the method can accomplish the accurate estimation of the velocity with efficient computation and good anti-noise performance and obtain the good HRRP simultaneously.
基金Project(61171133) supported by the National Natural Science Foundation of ChinaProject(11JJ1010) supported by the Natural Science Fund for Distinguished Young Scholars of Hunan Province,China
文摘The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.
基金Projects(11702235,51641905,41472269) supported by the National Natural Science Foundation of ChinaProject(2017JJ3290) supported by the Natural Science Foundation of Hunan Province,China+1 种基金Project(17C1540) supported by the Scientific Research Foundation of Education Department of Hunan Province,ChinaProject(16GES07) supported by the Open Research Fund of Hunan Key Laboratory of Geomechanics and Engineering Safety,China
文摘The particle simulation method is used to study the effects of loading waveforms （i.e. square, sinusoidal and triangle waveforms） on rock damage at mesoscopic scale. Then some influencing factors on rock damage at the mesoscopic scale, such as loading frequency, stress amplitude, mean stress, confining pressure and loading sequence, are also investigated with sinusoidal waveform in detail. The related numerical results have demonstrated that： 1） the loading waveform has a certain effect on rock failure processes. The square waveform has the most damage within these waveforms, while the triangle waveform has less damage than sinusoidal waveform. In each cycle, the number of microscopic cracks increases in the loading stage, while it keeps nearly constant in the unloading stage. 2） The loading frequency, stress amplitude, mean stress, confining pressure and loading sequence have considerable effects on rock damage subjected to cyclic loading. The higher the loading frequency, stress amplitude and mean stress, the greater the damage the rock accumulated; in contrast, the lower the confining pressure, the greater the damage the rock has accumulated. 3） There is a threshold value of mean stress and stress amplitude, below which no further damage accumulated after the first few cycle loadings. 4） The high-to-low loading sequence has more damage than the low-to-high loading sequence, suggesting that the rock damage is loading-path dependent.
基金supported by the National Natural Science Foundation of China(61671137)。
文摘Collocated multiple input multiple output(MIMO)radar,which has agile multi-beam working mode,can offer enhanced multiple targets tracking(MTT)ability.In detail,it can illuminate different targets simultaneously with multi-beam or one wide beam among multi-beam,providing greater degree of freedom in system resource control.An adaptive time-space resource and waveform control optimization model for the collocated MIMO radar with simultaneous multi-beam is proposed in this paper.The aim of the proposed scheme is to improve the overall tracking accuracy and meanwhile minimize the resource consumption under the guarantee of effective targets detection.A resource and waveform control algorithm which integrates the genetic algorithm(GA)is proposed to solve the optimization problem.The optimal transmitting waveform parameters,system sampling period,sub-array number,binary radar tracking parameterχ_i(t_k),transmitting energy and multi-beam direction vector combination are chosen adaptively,where the first one realizes the waveform control and the latter five realize the timespace resource allocation.Simulation results demonstrate the effectiveness of the proposed control method.
基金Project(2011D039)supported by Guangdong Innovative Research Team Program,China
文摘Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fixed threshold voltage value for gray scale display.In addition,the display has to repeatedly refresh between white and black states to eliminate ghost image when it needs to update a new image.The traditional driving waveform for the EPD includes four stages: erasing the original image,resetting to black state,clearing to white state,and writing a new image.A flicker can be found when transferring between two adjacent stages.A new driving waveform based on the improvement of activation pattern is proposed to weaken the ghost image and reduce the flicker.Experimental results show that the proposed driving waveform could weaken the ghost image effectively and reduce the number of flickers by 50%.Compared with the traditional driving waveform,the driving waveform of this work has a better performance.
基金Project supported by the Program for New Century Excellent Talents in University,ChinaProject(61171133)supported by the National Natural Science Foundation of China+2 种基金Project(11JJ1010)supported by the Natural Science Fund for Distinguished Young Scholars of Hunan Province,ChinaProject(61101182)supported by the National Natural Science Foundation for Young Scientists of ChinaProject(20124307110013)supported by the Doctoral Program of Higher Education of China
文摘The problems of joint adaptive waveform design and baseline range design for bistatic radar to maximize the practical radar resolution were considered.Distinguishing from the conventional ambiguity function(AF)-based resolution which is only related with the transmitted waveform and bistatic geometry and could be regarded as the potential resolution of a bistatic radar system,the practical resolution involves the effect of waveform,signal-to-noise ratio(SNR)as well as the measurement model.Thus,it is more practical and will have further significant application in target detection and tracking.The constraint optimization procedure of joint adaptive waveform design and baseline range design for maximizing the practical resolution of bistatic radar system under dynamic target scenario was devised.Simulation results show that the range and velocity resolution are enhanced according to the adaptive waveform and bistatic radar configuration.
基金This work was supported by the National Natural Science Foundation of China(91538201)the Taishan Scholar Project of Shandong Province(ts201511020)the project supported by Chinese National Key Laboratory of Science and Technology on Information System Security(6142111190404).
文摘Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.
文摘In this paper,218 long period Rayleigh wave records from 7 seismic station of CDSN are selected.We applied a partitioned waveform inversion to these data in order to construct a 3\|D model of shear velocity down to 400km depth in the crust and upper mantle of Qinghai\|Tibet plateau and Its Adjacent Regions (22°～44°N,70°～110°E).The first step of the waveform inversion used involved the matching of the waveforms of fundamental and highermost Ravleigh waves with waveforms synthesized from stratified models;in the second stage,the 3\|D model was constructed by solve linear constrains equation. The major structural features inferred from the surface waveform inversions can be summarized as follows:(1) There is a great contrast between surface waveform through Qinghai—Thibet plateau and the others.Main frequency of the former is lower than the latter, which indicate the crust depth of Qinghai—Tibet plateau is deeper than the others. In addition,the amplitude of about 30s period and 50s period is lower than both sides,which implied these exist lower velocity layer at about 25km depth and about 50km depth in Qinghai—Tibet plateau Crust.The former is common,the latter was argued because resolution of most method can not prove it.
文摘With the continuous improvement of radar intelligence, it is difficult for traditional countermeasures to achieve ideal results. In order to deal with complex, changeable, and unknown threat signals in the complex electromagnetic environment, a waveform intelligent optimization model based on intelligent optimization algorithm is proposed. By virtue of the universality and fast running speed of the intelligent optimization algorithm, the model can optimize the parameters used to synthesize the countermeasure waveform according to different external signals, so as to improve the countermeasure performance.Genetic algorithm(GA) and particle swarm optimization(PSO)are used to simulate the intelligent optimization of interruptedsampling and phase-modulation repeater waveform. The experimental results under different radar signal conditions show that the scheme is feasible. The performance comparison between the algorithms and some problems in the experimental results also provide a certain reference for the follow-up work.
基金This work was supported by the National Natural Science Foundation of China(62071440,61671241).
文摘In this paper, we propose a joint waveform selection and power allocation(JWSPA) strategy based on chance-constraint programming(CCP) for manned/unmanned aerial vehicle hybrid swarm(M/UAVHS) tracking a single target. Accordingly,the low probability of intercept(LPI) performance of system can be improved by collaboratively optimizing transmit power and waveform. For target radar cross section(RCS) prediction, we design a random RCS prediction model based on electromagnetic simulation(ES) of target. For waveform selection, we build a waveform library to adaptively manage the frequency modulation slope and pulse width of radar waveform. For power allocation,the CCP is employed to balance tracking accuracy and power resource. The Bayesian Cramér-Rao lower bound(BCRLB) is adopted as a criterion to measure target tracking accuracy. The hybrid intelli gent algorithms, in which the stochastic simulation is integrated into the genetic algorithm(GA), are used to solve the stochastic optimization problem. Simulation results demonstrate that the proposed JWSPA strategy can save more transmit power than the traditional fixed waveform scheme under the same target tracking accuracy.
基金supported by the National Natural Science Foundation of China(6107114561271331)
文摘For the issue of deterioration in detection performance caused by dynamically changing environment in ultra-wideband（UWB） multiple input multiple output（MIMO） radar, this paper proposes a novel adaptive waveform design which is aimed to improve the ability of discriminating target and clutter from the radar scene. Firstly, a sequence of Morlet wavelet pulses with frequency hopping and pulse position modulation by Welch-Costas array is designed. Then a waveform optimization solution is proposed which is achieved by applying the minimization mutual-information（MI） strategy. After that, with subsequent iterations of the algorithm, simulation results demonstrate that the optimal waveform design method brings an improvement in the target detection ability in the presence of noise and clutter.
基金Sponsored by National High-Tech Research and Development 863 Plan of China （2001AA415320） National Natural Science Foundation of China （69873007） Acknowledgement Hereon, we want to say thanks to colleagues who give support and advice to this paper, especially to engineers LIN Qin, HU Yong-yang, LU Zi-yi and HE Rong working at The 63rd Research Institute of General Staff, PLA University of Science and Technology.
