A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method ...A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method (TS-ESPRIT) is introduced. In order to realize the improved TS-ESPRIT, the proposed algorithm divides the planar array into multiple uniform sub-planar arrays with common reference point to get a unified phase shifts measurement point for all sub-arrays. The TS-ESPRIT is applied to each sub-array separately, and in the same time with the others to realize the parallelly temporal and spatial processing, so that it reduces the non-linearity effect of model and decreases the computational time. Then, the time difference of arrival (TDOA) technique is applied to combine the multiple sub-arrays in order to form the improved TS-ESPRIT. It is found that the proposed method achieves high accuracy at a low signal to noise ratio (SNR) with low computational complexity, leading to enhancement of the estimators performance.展开更多
In response to the demand for short-range detection of anti-smoke environment interference by laser fuzes,this study proposes a smoke environment simulation of non-uniform continuous point source diffusion and investi...In response to the demand for short-range detection of anti-smoke environment interference by laser fuzes,this study proposes a smoke environment simulation of non-uniform continuous point source diffusion and investigates an experimental laboratory smoke environment using an ammonium chloride smoke agent.The particle size distribution,composition,and mass flow distribution of the smoke were studied.Based on a discrete phase model and a kεturbulence model,a numerical simulation was developed to model the smoke generation and diffusion processes of the smoke agent in a confined space.The temporal and spatial distribution characteristics of the smoke mass concentration,velocity,and temperature in the space after smoke generation were analyzed,and the motion law governing the smoke diffusion throughout the entire space was summarized.Combined with the experimental verification of the smoke environment laboratory,the results showed that the smoke plume changed from fan-shaped to umbrella-shaped during smoke generation,and then continued to spread around.Meanwhile,the mass concentration of smoke in the space decreased from the middle outward;the changes in temperature and velocity were small and stable.In the diffusion stage(after 900 s),the mass concentration of smoke above 0.8 m was relatively uniform across an area of smoke that was 12 m thick.The concentration decreased over time,following a consistent decreasing trend,and the attenuation was negligible in a very short time.Therefore,this system was suitable for conducting experimental research on laser fuzes in a smoke environment.Owing to the stability of the equipment and facilities,the setup could reproduce the same experimental smoke environment by artificially controlling the smoke emission of the smoke agent.Overall,this work provides a theoretical reference for subsequent research efforts regarding the construction of uniform smoke environments and evaluating laser transmission characteristics in smoky environments.展开更多
The dynamic parameters of multiple projectiles that are fired using multi-barrel weapons in highfrequency continuous firing modes are important indicators to measure the performance of these weapons.The characteristic...The dynamic parameters of multiple projectiles that are fired using multi-barrel weapons in highfrequency continuous firing modes are important indicators to measure the performance of these weapons.The characteristics of multiple projectiles are high randomness and large numbers launched in a short period of time,making it very difficult to obtain the real dispersion parameters of the projectiles due to the occlusion or coincidence of multiple projectiles.Using six intersecting-screen testing system,in this paper,we propose an association recognition and matching algorithm of multiple projectiles using a temporal and spatial information constraint mechanism.We extract the output signal from each detection screen and then use the wavelet transform to process the output signal.We present a method to identify and extract the time values on which the projectiles pass through the detection screens using the wavelet transform modulus maximum theory.We then use the correlation of the output signals of three parallel detection screens to establish a correlation coefficient recognition constraint function for the multiple projectiles.Based on the premise of linear projectile motion,we establish a temporal and spatial constraint matching model using the projectile’s position coordinates in each detection screen and the projectile’s time constraints within the multiple intersecting-screen geometry.We then determine the time values of the multiple projectiles in each detection screen using an iterative search cycle registration,and finally obtain the flight parameters for the multiple projectiles in the presence of uncertainty.The proposed method and algorithm were verified experimentally and can solve the problem of uncertainty in projectiles flight parameter under different multiple projectile firing states.展开更多
To enhance the resolution of parameter estimation with limited samples received by a short passive array, an iterative nonparametric algorithm for estimating the frequencies and direction-of-arrivals （DOAs） of signa...To enhance the resolution of parameter estimation with limited samples received by a short passive array, an iterative nonparametric algorithm for estimating the frequencies and direction-of-arrivals （DOAs） of signals is proposed. The cost function is constructed using 12-norm Gaussian entropy combined with an additional constraint, 12-norm constraint or linear constraint. By minimizing the cost functions in the temporal and the spatial dimensions using corresponding iteration algorithms respectively, the sparse discrete Fourier transforms （DFTs） of temporal and spatial samples are obtained to represent the extrapolated sequences with much larger sizes than the original samples. Then frequency and angle estimates are obtained by performing the traditional simple methods on the extrapolated sequences. It is shown that the proposed algorithm offers increased resolution and significantly reduced sidelobes compared with the periodogram and beamforming based methods. And it achieves high precision compared with the high-resolution method with lower computational burden. Some numerical simulations and real data processing results are presented to verify the effectiveness of the method.展开更多
Improving crop water productivity is necessary for ensuring food security. To quantify the water utilization in grain production from multiple perspectives, gross inflow water productivity(WPg), generalized agricultur...Improving crop water productivity is necessary for ensuring food security. To quantify the water utilization in grain production from multiple perspectives, gross inflow water productivity(WPg), generalized agricultural water productivity(WPa), evapotranspiration water productivity(WPET) and irrigation water productivity(WPI) were examined in this study. This paper calculated and analyzed the temporal and spatial variation in these water productivity(WP) indices in the irrigated land of Heilongjiang Province. The results showed that almost all of the municipal WP indices increased from 2007 to 2015. The four indices showed large differences in scientific connotation and numerical performance, and their degrees of spatial variation were ranked as WPI>WPa>WPg>WPET. The spatial patterns of WP indices in different years were similar; the central and southern regions on the Songnen Plain and the eastern region had high WP values, while those of the northern region were low. Each WP index was used to evaluate the relationship between the input of water resources and the output of grain between different regions. Most cities had the potential to improve WP by reducing the input of irrigation water. Furthermore, the results provided recommendations to decision makers to plan for efficient use of water resources in different cities.展开更多
In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the tempor...In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the temporal correlation, spatial correlation and historical correlation, a basic DTTS model is built. And a three-stage approach is put forward for the simplification and calibration of the basic DTTS model. Through critical sections pre-selection and critical time pre-selection, the first stage reduces the variable number of the basic DTTS model. In the second stage, variable coefficient calibration is implemented based on basic model simplification and stepwise regression analysis. Aimed at dynamic noise estimation, the characteristics of noise are summarized and an extreme learning machine is presented in the third stage. A case study based on a real-world road network in Beijing, China, is carried out to test the efficiency and applicability of proposed DTTS model and the three-stage approach.展开更多
How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image re...How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.展开更多
Owing to the wide range of applications in various fields,generative models have become increasingly popular.However,they do not handle spatio-temporal features well.Inspired by the recent advances in these models,thi...Owing to the wide range of applications in various fields,generative models have become increasingly popular.However,they do not handle spatio-temporal features well.Inspired by the recent advances in these models,this paper designs a distributed spatio-temporal generative adversarial network(STGAN-D)that,given some initial data and random noise,generates a consecutive sequence of spatio-temporal samples which have a logical relationship.This paper builds a spatio-temporal discriminator to distinguish whether the samples generated by the generator meet the requirements for time and space coherence,and builds a controller for distributed training of the network gradient updated to separate the model training and parameter updating,to improve the network training rate.The model is trained on the skeletal dataset and the traffic dataset.In contrast to traditional generative adversarial networks(GANs),the proposed STGAN-D can generate logically coherent samples with the corresponding spatial and temporal features while avoiding mode collapse.In addition,this paper shows that the proposed model can generate different styles of spatio-temporal samples given different random noise inputs,and the controller can improve the network training rate.This model will extend the potential range of applications of GANs to areas such as traffic information simulation and multiagent adversarial simulation.展开更多
基金supported by the National Natural Science Foundation of China(61301211)and the Aviation Science Foundation(20131852028)
文摘A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method (TS-ESPRIT) is introduced. In order to realize the improved TS-ESPRIT, the proposed algorithm divides the planar array into multiple uniform sub-planar arrays with common reference point to get a unified phase shifts measurement point for all sub-arrays. The TS-ESPRIT is applied to each sub-array separately, and in the same time with the others to realize the parallelly temporal and spatial processing, so that it reduces the non-linearity effect of model and decreases the computational time. Then, the time difference of arrival (TDOA) technique is applied to combine the multiple sub-arrays in order to form the improved TS-ESPRIT. It is found that the proposed method achieves high accuracy at a low signal to noise ratio (SNR) with low computational complexity, leading to enhancement of the estimators performance.
基金the Central University Special Funding for Basic Scientific Research(Grant No.30918012201)the Foundation of JWKJW Field(Grant 2020-JCJQ-JJ-392)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX20_0315).
文摘In response to the demand for short-range detection of anti-smoke environment interference by laser fuzes,this study proposes a smoke environment simulation of non-uniform continuous point source diffusion and investigates an experimental laboratory smoke environment using an ammonium chloride smoke agent.The particle size distribution,composition,and mass flow distribution of the smoke were studied.Based on a discrete phase model and a kεturbulence model,a numerical simulation was developed to model the smoke generation and diffusion processes of the smoke agent in a confined space.The temporal and spatial distribution characteristics of the smoke mass concentration,velocity,and temperature in the space after smoke generation were analyzed,and the motion law governing the smoke diffusion throughout the entire space was summarized.Combined with the experimental verification of the smoke environment laboratory,the results showed that the smoke plume changed from fan-shaped to umbrella-shaped during smoke generation,and then continued to spread around.Meanwhile,the mass concentration of smoke in the space decreased from the middle outward;the changes in temperature and velocity were small and stable.In the diffusion stage(after 900 s),the mass concentration of smoke above 0.8 m was relatively uniform across an area of smoke that was 12 m thick.The concentration decreased over time,following a consistent decreasing trend,and the attenuation was negligible in a very short time.Therefore,this system was suitable for conducting experimental research on laser fuzes in a smoke environment.Owing to the stability of the equipment and facilities,the setup could reproduce the same experimental smoke environment by artificially controlling the smoke emission of the smoke agent.Overall,this work provides a theoretical reference for subsequent research efforts regarding the construction of uniform smoke environments and evaluating laser transmission characteristics in smoky environments.
基金been supported by Project of the National Natural Science Foundation of China(No.62073256)the Shaanxi Provincial Science and Technology Department(No.2020GY-125)Xi’an Science and Technology Innovation talent service enterprise project(No.2020KJRC0041)。
文摘The dynamic parameters of multiple projectiles that are fired using multi-barrel weapons in highfrequency continuous firing modes are important indicators to measure the performance of these weapons.The characteristics of multiple projectiles are high randomness and large numbers launched in a short period of time,making it very difficult to obtain the real dispersion parameters of the projectiles due to the occlusion or coincidence of multiple projectiles.Using six intersecting-screen testing system,in this paper,we propose an association recognition and matching algorithm of multiple projectiles using a temporal and spatial information constraint mechanism.We extract the output signal from each detection screen and then use the wavelet transform to process the output signal.We present a method to identify and extract the time values on which the projectiles pass through the detection screens using the wavelet transform modulus maximum theory.We then use the correlation of the output signals of three parallel detection screens to establish a correlation coefficient recognition constraint function for the multiple projectiles.Based on the premise of linear projectile motion,we establish a temporal and spatial constraint matching model using the projectile’s position coordinates in each detection screen and the projectile’s time constraints within the multiple intersecting-screen geometry.We then determine the time values of the multiple projectiles in each detection screen using an iterative search cycle registration,and finally obtain the flight parameters for the multiple projectiles in the presence of uncertainty.The proposed method and algorithm were verified experimentally and can solve the problem of uncertainty in projectiles flight parameter under different multiple projectile firing states.
基金supported by the Program for New Century Excellent Talents in University (NCET-06-0856)the National Natural Science Foundation of China (60772068)
文摘To enhance the resolution of parameter estimation with limited samples received by a short passive array, an iterative nonparametric algorithm for estimating the frequencies and direction-of-arrivals （DOAs） of signals is proposed. The cost function is constructed using 12-norm Gaussian entropy combined with an additional constraint, 12-norm constraint or linear constraint. By minimizing the cost functions in the temporal and the spatial dimensions using corresponding iteration algorithms respectively, the sparse discrete Fourier transforms （DFTs） of temporal and spatial samples are obtained to represent the extrapolated sequences with much larger sizes than the original samples. Then frequency and angle estimates are obtained by performing the traditional simple methods on the extrapolated sequences. It is shown that the proposed algorithm offers increased resolution and significantly reduced sidelobes compared with the periodogram and beamforming based methods. And it achieves high precision compared with the high-resolution method with lower computational burden. Some numerical simulations and real data processing results are presented to verify the effectiveness of the method.
基金Supported by National Natural Science Foundation of China(51479032)National Key R&D Plan(2017YFC0406002)
文摘Improving crop water productivity is necessary for ensuring food security. To quantify the water utilization in grain production from multiple perspectives, gross inflow water productivity(WPg), generalized agricultural water productivity(WPa), evapotranspiration water productivity(WPET) and irrigation water productivity(WPI) were examined in this study. This paper calculated and analyzed the temporal and spatial variation in these water productivity(WP) indices in the irrigated land of Heilongjiang Province. The results showed that almost all of the municipal WP indices increased from 2007 to 2015. The four indices showed large differences in scientific connotation and numerical performance, and their degrees of spatial variation were ranked as WPI>WPa>WPg>WPET. The spatial patterns of WP indices in different years were similar; the central and southern regions on the Songnen Plain and the eastern region had high WP values, while those of the northern region were low. Each WP index was used to evaluate the relationship between the input of water resources and the output of grain between different regions. Most cities had the potential to improve WP by reducing the input of irrigation water. Furthermore, the results provided recommendations to decision makers to plan for efficient use of water resources in different cities.
基金Project(2014BAG01B0403)supported by the National High-Tech Research and Development Program of China
文摘In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the temporal correlation, spatial correlation and historical correlation, a basic DTTS model is built. And a three-stage approach is put forward for the simplification and calibration of the basic DTTS model. Through critical sections pre-selection and critical time pre-selection, the first stage reduces the variable number of the basic DTTS model. In the second stage, variable coefficient calibration is implemented based on basic model simplification and stepwise regression analysis. Aimed at dynamic noise estimation, the characteristics of noise are summarized and an extreme learning machine is presented in the third stage. A case study based on a real-world road network in Beijing, China, is carried out to test the efficiency and applicability of proposed DTTS model and the three-stage approach.
文摘How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.
基金the National Natural Science Foundation of China(61573285).
文摘Owing to the wide range of applications in various fields,generative models have become increasingly popular.However,they do not handle spatio-temporal features well.Inspired by the recent advances in these models,this paper designs a distributed spatio-temporal generative adversarial network(STGAN-D)that,given some initial data and random noise,generates a consecutive sequence of spatio-temporal samples which have a logical relationship.This paper builds a spatio-temporal discriminator to distinguish whether the samples generated by the generator meet the requirements for time and space coherence,and builds a controller for distributed training of the network gradient updated to separate the model training and parameter updating,to improve the network training rate.The model is trained on the skeletal dataset and the traffic dataset.In contrast to traditional generative adversarial networks(GANs),the proposed STGAN-D can generate logically coherent samples with the corresponding spatial and temporal features while avoiding mode collapse.In addition,this paper shows that the proposed model can generate different styles of spatio-temporal samples given different random noise inputs,and the controller can improve the network training rate.This model will extend the potential range of applications of GANs to areas such as traffic information simulation and multiagent adversarial simulation.
