A novel subspace projection anti-jamming algorithm based on spatial blind search is proposed,which uses multiple single-constrained subspace projection parallel filters.If the direction of arrival(DOA)of a satellite s...A novel subspace projection anti-jamming algorithm based on spatial blind search is proposed,which uses multiple single-constrained subspace projection parallel filters.If the direction of arrival(DOA)of a satellite signal is unknown,the traditional subspace projection anti-jamming algorithm cannot form the correct beam pointing.To overcome the problem of the traditional subspace projection algorithm,multiple single-constrained subspace projection parallel filters are used.Every single-constrained anti-jamming subspace projection algorithm obtains the optimal weight vector by searching the DOA of the satellite signal and uses the output of cross correlation as a decision criterion.Test results show that the algorithm can suppress the jamming effectively,and generate high gain toward the desired signal.The research provides a new idea for the engineering implementation of a multi-beam anti-jamming algorithm based on subspace projection.展开更多
Differential spatial modulation(DSM)is a multiple-input multiple-output(MIMO)transmission scheme.It has attracted extensive research interest due to its ability to transmit additional data without increasing any radio...Differential spatial modulation(DSM)is a multiple-input multiple-output(MIMO)transmission scheme.It has attracted extensive research interest due to its ability to transmit additional data without increasing any radio frequency chain.In this paper,DSM is investigated using two mapping algorithms:Look-Up Table Order(LUTO)and Permutation Method(PM).Then,the bit error rate(BER)performance and complexity of the two mapping algorithms in various antennas and modulation methods are verified by simulation experiments.The results show that PM has a lower BER than the LUTO mapping algorithm,and the latter has lower complexity than the former.展开更多
A general regression neural network model,combined with an interative algorithm(GRNNI)using sparsely distributed samples and auxiliary environmental variables was proposed to predict both spatial distribution and vari...A general regression neural network model,combined with an interative algorithm(GRNNI)using sparsely distributed samples and auxiliary environmental variables was proposed to predict both spatial distribution and variability of soil organic matter(SOM)in a bamboo forest.The auxiliary environmental variables were:elevation,slope,mean annual temperature,mean annual precipitation,and normalized difference vegetation index.The prediction accuracy of this model was assessed via three accuracy indices,mean error(ME),mean absolute error(MAE),and root mean squared error(RMSE)for validation in sampling sites.Both the prediction accuracy and reliability of this model were compared to those of regression kriging(RK)and ordinary kriging(OK).The results show that the prediction accuracy of the GRNNI model was higher than that of both RK and OK.The three accuracy indices(ME,MAE,and RMSE)of the GRNNI model were lower than those of RK and OK.Relative improvements of RMSE of the GRNNI model compared with RK and OK were 13.6%and 17.5%,respectively.In addition,a more realistic spatial pattern of SOM was produced by the model because the GRNNI model was more suitable than multiple linear regression to capture the nonlinear relationship between SOM and the auxiliary environmental variables.Therefore,the GRNNI model can improve both prediction accuracy and reliability for determining spatial distribution and variability of SOM.展开更多
The behind-armor debris(BAD) formed by the perforation of an EFP is the main damage factor for the secondary destruction to the behind-armor components.Aiming at investigating the BAD caused by EFP,flash X-ray radiogr...The behind-armor debris(BAD) formed by the perforation of an EFP is the main damage factor for the secondary destruction to the behind-armor components.Aiming at investigating the BAD caused by EFP,flash X-ray radiography combined with an experimental witness plate test method was used,and the FEM-SPH adaptive conversion algorithm in LS-DYNA software was erployed to model the perforation process.The simulation results of the debris cloud shape and number of debris were in good agreement with the flash X-ray radiographs and perforated holes on the witness plate,respectlvely.Threedimensional numerical simulations of EFP's penetration under various impact conditions were conducted.The results show that,an ellipsoidal debris cloud,with the major-to-minor axis radio(a/b)smaller than that caused by shaped charge jets,was formed behind the target.With the increase of target thickness(h) and decrease of impact velocity(v_0) and obliquity(θ),the value of a/b decreases.The number of debris ejected from target is significantly higher than that from EFP.Based on the statistical analysis of the spatial distribution of the BAD,An engineering calculation model was established considering the influence of h,v_0 and θ.The model can with reasonable accuracy predict the quantity and velocity distribution characteristics of BAD formed by EFP.展开更多
To reduce the error from measurement and retrieval process, a new technology of spatial heterodyne spectroscopy is proposed. The principle of this technology and the instrument spatial het- erodyne spectrometer (SHS...To reduce the error from measurement and retrieval process, a new technology of spatial heterodyne spectroscopy is proposed. The principle of this technology and the instrument spatial het- erodyne spectrometer (SHS) are introduced. The first application of this technology will be for CO2 measurements from space on a high spectral observation satellite. The outstanding measurement principle and the priority of combination of retrieval algorithm and three channels ( O2 A-band, CO2 1.58 μm and 2.06 μm bands) are theoretically analyzed and numerically simulated. Experiments u- sing SHS prototype with low spectral resolution of 0. 4 cm -1are carried out for preliminary valida- tion. The measurements show clear CO2 absorption lines and follow the expected signature with the- ory spectrum, and the retrievals agreed well with GOSAT CO2 products, except a small bias of about 4 × 10 ^-6. The results show that the ability of spatial heterodyne spectroscopy for CO2 detecting is ob- vious, and SHS is a competent sensor.展开更多
A quick and accurate extraction of dominant colors of background images is the basis of adaptive camouflage design.This paper proposes a Color Image Quick Fuzzy C-Means(CIQFCM)clustering algorithm based on clustering ...A quick and accurate extraction of dominant colors of background images is the basis of adaptive camouflage design.This paper proposes a Color Image Quick Fuzzy C-Means(CIQFCM)clustering algorithm based on clustering spatial mapping.First,the clustering sample space was mapped from the image pixels to the quantized color space,and several methods were adopted to compress the amount of clustering samples.Then,an improved pedigree clustering algorithm was applied to obtain the initial class centers.Finally,CIQFCM clustering algorithm was used for quick extraction of dominant colors of background image.After theoretical analysis of the effect and efficiency of the CIQFCM algorithm,several experiments were carried out to discuss the selection of proper quantization intervals and to verify the effect and efficiency of the CIQFCM algorithm.The results indicated that the value of quantization intervals should be set to 4,and the proposed algorithm could improve the clustering efficiency while maintaining the clustering effect.In addition,as the image size increased from 128×128 to 1024×1024,the efficiency improvement of CIQFCM algorithm was increased from 6.44 times to 36.42 times,which demonstrated the significant advantage of CIQFCM algorithm in dominant colors extraction of large-size images.展开更多
Without any prior information about related wireless transmitting nodes,joint estimation of the position and power of a blind signal combined with multiple co-frequency radio waves is a challenging task.Measuring the ...Without any prior information about related wireless transmitting nodes,joint estimation of the position and power of a blind signal combined with multiple co-frequency radio waves is a challenging task.Measuring the signal related data based on a group distributed sensor is an efficient way to infer the various characteristics of the signal sources.In this paper,we propose a particle swarm optimization to estimate multiple co-frequency"blind"source nodes,which is based on the received power data measured by the sensors.To distract the mix signals precisely,a genetic algorithm is applied,and it further improves the estimation performance of the system.The simulation results show the efficiency of the proposed algorithm.展开更多
In this paper,the conventional method of establishing spatial channel models(SCMs)based on measurements is extended by including clusters-of-scatterers(CoSs)that exist along propagation paths.The channel models result...In this paper,the conventional method of establishing spatial channel models(SCMs)based on measurements is extended by including clusters-of-scatterers(CoSs)that exist along propagation paths.The channel models resulted utilizing this new method are applicable for generating channel realizations of reasonable spatial consistency,which is required for designing techniques and systems of the fifth generation wireless communications.The scatterers’locations are estimated from channel measurement data obtained using large-scale antenna arrays through the Space-Alternating Generalized Expectation-Maximization(SAGE)algorithm derived under a spherical wavefront assumption.The stochastic properties of CoSs extracted from real measurement data in an indoor environment are presented.展开更多
基金Supported by the Natural Science Foundation of Hebei Province(F2011205023)the National Natural Science Foundation of China(61175059)。
文摘A novel subspace projection anti-jamming algorithm based on spatial blind search is proposed,which uses multiple single-constrained subspace projection parallel filters.If the direction of arrival(DOA)of a satellite signal is unknown,the traditional subspace projection anti-jamming algorithm cannot form the correct beam pointing.To overcome the problem of the traditional subspace projection algorithm,multiple single-constrained subspace projection parallel filters are used.Every single-constrained anti-jamming subspace projection algorithm obtains the optimal weight vector by searching the DOA of the satellite signal and uses the output of cross correlation as a decision criterion.Test results show that the algorithm can suppress the jamming effectively,and generate high gain toward the desired signal.The research provides a new idea for the engineering implementation of a multi-beam anti-jamming algorithm based on subspace projection.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant No.62061024the Project of Gansu Province Science and Technology Department under Grant No.22ZD6GA055.
文摘Differential spatial modulation(DSM)is a multiple-input multiple-output(MIMO)transmission scheme.It has attracted extensive research interest due to its ability to transmit additional data without increasing any radio frequency chain.In this paper,DSM is investigated using two mapping algorithms:Look-Up Table Order(LUTO)and Permutation Method(PM).Then,the bit error rate(BER)performance and complexity of the two mapping algorithms in various antennas and modulation methods are verified by simulation experiments.The results show that PM has a lower BER than the LUTO mapping algorithm,and the latter has lower complexity than the former.
基金The article is supported by National Key Research and Development Projects of P.R.China(No.2018YFD0600100).
文摘A general regression neural network model,combined with an interative algorithm(GRNNI)using sparsely distributed samples and auxiliary environmental variables was proposed to predict both spatial distribution and variability of soil organic matter(SOM)in a bamboo forest.The auxiliary environmental variables were:elevation,slope,mean annual temperature,mean annual precipitation,and normalized difference vegetation index.The prediction accuracy of this model was assessed via three accuracy indices,mean error(ME),mean absolute error(MAE),and root mean squared error(RMSE)for validation in sampling sites.Both the prediction accuracy and reliability of this model were compared to those of regression kriging(RK)and ordinary kriging(OK).The results show that the prediction accuracy of the GRNNI model was higher than that of both RK and OK.The three accuracy indices(ME,MAE,and RMSE)of the GRNNI model were lower than those of RK and OK.Relative improvements of RMSE of the GRNNI model compared with RK and OK were 13.6%and 17.5%,respectively.In addition,a more realistic spatial pattern of SOM was produced by the model because the GRNNI model was more suitable than multiple linear regression to capture the nonlinear relationship between SOM and the auxiliary environmental variables.Therefore,the GRNNI model can improve both prediction accuracy and reliability for determining spatial distribution and variability of SOM.
基金supported by National Natural Science Foundation of China(Grant no.11872123)。
文摘The behind-armor debris(BAD) formed by the perforation of an EFP is the main damage factor for the secondary destruction to the behind-armor components.Aiming at investigating the BAD caused by EFP,flash X-ray radiography combined with an experimental witness plate test method was used,and the FEM-SPH adaptive conversion algorithm in LS-DYNA software was erployed to model the perforation process.The simulation results of the debris cloud shape and number of debris were in good agreement with the flash X-ray radiographs and perforated holes on the witness plate,respectlvely.Threedimensional numerical simulations of EFP's penetration under various impact conditions were conducted.The results show that,an ellipsoidal debris cloud,with the major-to-minor axis radio(a/b)smaller than that caused by shaped charge jets,was formed behind the target.With the increase of target thickness(h) and decrease of impact velocity(v_0) and obliquity(θ),the value of a/b decreases.The number of debris ejected from target is significantly higher than that from EFP.Based on the statistical analysis of the spatial distribution of the BAD,An engineering calculation model was established considering the influence of h,v_0 and θ.The model can with reasonable accuracy predict the quantity and velocity distribution characteristics of BAD formed by EFP.
基金Supported by the National Natural Science Foundation of China(41175037)
文摘To reduce the error from measurement and retrieval process, a new technology of spatial heterodyne spectroscopy is proposed. The principle of this technology and the instrument spatial het- erodyne spectrometer (SHS) are introduced. The first application of this technology will be for CO2 measurements from space on a high spectral observation satellite. The outstanding measurement principle and the priority of combination of retrieval algorithm and three channels ( O2 A-band, CO2 1.58 μm and 2.06 μm bands) are theoretically analyzed and numerically simulated. Experiments u- sing SHS prototype with low spectral resolution of 0. 4 cm -1are carried out for preliminary valida- tion. The measurements show clear CO2 absorption lines and follow the expected signature with the- ory spectrum, and the retrievals agreed well with GOSAT CO2 products, except a small bias of about 4 × 10 ^-6. The results show that the ability of spatial heterodyne spectroscopy for CO2 detecting is ob- vious, and SHS is a competent sensor.
文摘A quick and accurate extraction of dominant colors of background images is the basis of adaptive camouflage design.This paper proposes a Color Image Quick Fuzzy C-Means(CIQFCM)clustering algorithm based on clustering spatial mapping.First,the clustering sample space was mapped from the image pixels to the quantized color space,and several methods were adopted to compress the amount of clustering samples.Then,an improved pedigree clustering algorithm was applied to obtain the initial class centers.Finally,CIQFCM clustering algorithm was used for quick extraction of dominant colors of background image.After theoretical analysis of the effect and efficiency of the CIQFCM algorithm,several experiments were carried out to discuss the selection of proper quantization intervals and to verify the effect and efficiency of the CIQFCM algorithm.The results indicated that the value of quantization intervals should be set to 4,and the proposed algorithm could improve the clustering efficiency while maintaining the clustering effect.In addition,as the image size increased from 128×128 to 1024×1024,the efficiency improvement of CIQFCM algorithm was increased from 6.44 times to 36.42 times,which demonstrated the significant advantage of CIQFCM algorithm in dominant colors extraction of large-size images.
文摘Without any prior information about related wireless transmitting nodes,joint estimation of the position and power of a blind signal combined with multiple co-frequency radio waves is a challenging task.Measuring the signal related data based on a group distributed sensor is an efficient way to infer the various characteristics of the signal sources.In this paper,we propose a particle swarm optimization to estimate multiple co-frequency"blind"source nodes,which is based on the received power data measured by the sensors.To distract the mix signals precisely,a genetic algorithm is applied,and it further improves the estimation performance of the system.The simulation results show the efficiency of the proposed algorithm.
基金jointly supported by the key project “5G Ka frequency bands and higher and lower frequency band cooperative trail system research and development” of China Ministry of Industry and Information Technology under Grant number 2016ZX03001015the Hong Kong,Macao and Taiwan Science&Technology Cooperation Program of China under Grant No.2014DFT10290.
文摘In this paper,the conventional method of establishing spatial channel models(SCMs)based on measurements is extended by including clusters-of-scatterers(CoSs)that exist along propagation paths.The channel models resulted utilizing this new method are applicable for generating channel realizations of reasonable spatial consistency,which is required for designing techniques and systems of the fifth generation wireless communications.The scatterers’locations are estimated from channel measurement data obtained using large-scale antenna arrays through the Space-Alternating Generalized Expectation-Maximization(SAGE)algorithm derived under a spherical wavefront assumption.The stochastic properties of CoSs extracted from real measurement data in an indoor environment are presented.