An improved two-channel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) method based on eigen-decomposition of the covariance matrix is investigated. Based on the joint Probability Density Function...An improved two-channel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) method based on eigen-decomposition of the covariance matrix is investigated. Based on the joint Probability Density Function (PDF) of the Along-Track Interferometric (ATI) phase and the similarity between the two SAR complex images, a novel ellipse detector is presented and is applied to the indication of ground moving targets. We derive its statistics and analyze the performance of detection process in detail. Compared with the approach using the ATI phase, the ellipse detector has a better performance of detection in homogenous clutter. Numerical experiments on simulated data are presented to validate the improved performance of the ellipse detector with respect to the ATI phase approach. Finally, the detection capability of the proposed method is demonstrated by measured SAR data.展开更多
In this paper,we consider the limiting spectral distribution of the information-plus-noise type sample covariance matrices Cn=1/N（Rn＋σXn）（Rn＋σXn）,under the assumption that the entries of Xn are independent but...In this paper,we consider the limiting spectral distribution of the information-plus-noise type sample covariance matrices Cn=1/N（Rn＋σXn）（Rn＋σXn）,under the assumption that the entries of Xn are independent but non-identically distributed random variables.It is proved that,almost surely,the empirical spectral distribution of Cn converges weakly to a non-random distribution whose Stieltjes transform satisfies a certain equation.Our result extends the previous one with the entries of Xn are i.i.d.random varibles to a more general case.The proof of the result mainly employs the Stein equation and the cumulant expansion formula of independent random variables.展开更多
The performance evaluation of automatic carrier landing system(ACLS)is an important part in the field of carrier aircraft landing control.Combining grey analytic hierarchy theory and data normalization theory,an impro...The performance evaluation of automatic carrier landing system(ACLS)is an important part in the field of carrier aircraft landing control.Combining grey analytic hierarchy theory and data normalization theory,an improved grey analytic hierarchy method is introduced to evaluate the performance of ACLS.A complete performance evaluation indicators system of ACLS is established,and the definition and calculation formula of each indicator are provided.The grey analytic hierarchy model is modified to improve the real-time performance of the algorithm,where traditional expert scoring sampling matrix is substituted by an indicator normalized sample matrix.Taking a certain ACLS as an example,the experimental simulation is carried out,and the simulation results verify the reliability and the accuracy of the improved grey analytic hierarchy method.展开更多
In actual exploration,the demand for 3D seismic data collection is increasing,and the requirements for data are becoming higher and higher.Accordingly,the collection cost and data volume also increase.Aiming at this p...In actual exploration,the demand for 3D seismic data collection is increasing,and the requirements for data are becoming higher and higher.Accordingly,the collection cost and data volume also increase.Aiming at this problem,we make use of the nature of data sparse expression,based on the theory of compressed sensing,to carry out the research on the efficient collection method of seismic data.It combines the collection of seismic data and the compression in data processing in practical work,breaking through the limitation of the traditional sampling frequency,and the sparse characteristics of the seismic signal are utilized to reconstruct the missing data.We focus on the key elements of the sampling matrix in the theory of compressed sensing,and study the methods of seismic data acquisition.According to the conditions that the compressed sensing sampling matrix needs to meet,we introduce a new random acquisition scheme,which introduces the widely used Low-density Parity-check(LDPC)sampling matrix in image processing into seismic exploration acquisition.Firstly,its properties are discussed and its conditions for satisfying the sampling matrix in compressed sensing are verified.Then the LDPC sampling method and the conventional data acquisition method are used to synthesize seismic data reconstruction experiments.The reconstruction results,signal-to-noise ratio and reconstruction error are compared to verify the seismic data based on sparse constraints.The LDPC sampling method improves the current seismic data reconstruction efficiency,reduces the exploration cost and the effectiveness and feasibility of the method.展开更多
In order to solve the problem of high-speed sampling in OFDM based ultra wide band(UWB) systems, this paper first gives analysis on the applicability of existing compressed sampling methods. Then, on the basis of an e...In order to solve the problem of high-speed sampling in OFDM based ultra wide band(UWB) systems, this paper first gives analysis on the applicability of existing compressed sampling methods. Then, on the basis of an established segmented observation model, it presents an optimized parallel segmented compressed sampling(OPSCS) scheme based on Hadamard matrix. The orthogonal Hadamard matrix is adopted to construct the segmented measurement matrix with any dimensions, thus orthogonal or quasi-orthogonal multiplex observation sequences are obtained, and the restricted isometry property is improved. The optimized orthogonal matching pursuit algorithm is also used for the known sparsity avoiding iterative operation. Researches show that the proposed method can effectively reduce the sampling rate in OFDM-UWB systems, and also has a good ability of noise resisting that it achieves a high system performance better than the existing schemes of compressed sampling and even Nyquist rate sampling.展开更多
Let {vij}, i, j = 1, 2, …, be i.i.d, random variables with Ev11 = 0, Ev11^2 = 1 and a1 = （ai1,…, aiM） be random vectors with {aij} being i.i.d, random variables. Define XN =（x1,…, xk） and SN =XNXN^T,where xi=ai...Let {vij}, i, j = 1, 2, …, be i.i.d, random variables with Ev11 = 0, Ev11^2 = 1 and a1 = （ai1,…, aiM） be random vectors with {aij} being i.i.d, random variables. Define XN =（x1,…, xk） and SN =XNXN^T,where xi=ai×si and si=1/√N（v1i,…, vN,i）^T. The spectral distribution of SN is proven to converge, with probability one, to a nonrandom distribution function under mild conditions.展开更多
Wireless Communication is a system for communicating information from one point to other,without utilizing any connections like wire,cable,or other physical medium.Cognitive Radio(CR)based systems and networks are a r...Wireless Communication is a system for communicating information from one point to other,without utilizing any connections like wire,cable,or other physical medium.Cognitive Radio(CR)based systems and networks are a revolutionary new perception in wireless communications.Spectrum sensing is a vital task of CR to avert destructive intrusion with licensed primary or main users and discover the accessible spectrum for the efficient utilization of the spectrum.Centralized Cooperative Spectrum Sensing(CSS)is a kind of spectrum sensing.Most of the test metrics designed till now for sensing the spectrum is produced by using the Sample Covariance Matrix(SCM)of the received signal.Some of the methods that use the SCM for the process of detection are Pietra-Ricci Index Detector(PRIDe),Hadamard Ratio(HR)detector,Gini Index Detector(GID),etc.This paper presents the simulation and comparative perfor-mance analysis of PRIDe with various other detectors like GID,HR,Arithmetic to Geometric Mean(AGM),Volume-based Detector number 1(VD1),Maximum-to-Minimum Eigenvalue Detection(MMED),and Generalized Likelihood Ratio Test(GLRT)using the MATLAB software.The PRIDe provides better performance in the presence of variations in the power of the signal and the noise power with less computational complexity.展开更多
After the implementation of ultra-low emission policies,the pollutant emissions from the coal-fired power generation systems in China have been further reduced,which creates more critical requirements for the control ...After the implementation of ultra-low emission policies,the pollutant emissions from the coal-fired power generation systems in China have been further reduced,which creates more critical requirements for the control accuracies of denitrification systems using selective catalytic reduction technology and controls of ammonia slip.This article presents big data-based technologies for controlling ammonia slip,through precise ammonia injections,which were applied and demonstrated for a flue gas denitrification system of a Chinese coal-fired power plant.Through examinations and analyses of the basic operating conditions of the unit and parameters,such as NOx emission control efficiency,ammonia injection amount of the denitrification system,and non-uniformity of NOx concentrations in the denitrification zone were compared before and after the implementation of these technologies,the outcome proves that this artificial intelligence algorithm based on big data can effectively solve the automatic control problem of denitrification system under complex working conditions such as varied unit loads,day and night operation changed coal source.In addition to the effective controls of the ammonia slip of the system,the controls of NOx emission of the system become more stabilized,creating a successful example for wider applications of these precise ammonia injection control technologies in the future.Analyses show that NOx non-uniformities can be reduced by more than 50%under both stable and variable load conditions.NOx fluctuations at the unit outlet are tightly controlled within±10 mg/Nm^(3) under variable load conditions and within±5 mg/Nm^(3) under stable conditions.The average ammonia injection amounts under various load conditions have decreased by 15.7%.展开更多
基金Supported by the Aviation Science Fund (No. 20080152004)China Postdoctoral Foundation (No. 20090461119)
文摘An improved two-channel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) method based on eigen-decomposition of the covariance matrix is investigated. Based on the joint Probability Density Function (PDF) of the Along-Track Interferometric (ATI) phase and the similarity between the two SAR complex images, a novel ellipse detector is presented and is applied to the indication of ground moving targets. We derive its statistics and analyze the performance of detection process in detail. Compared with the approach using the ATI phase, the ellipse detector has a better performance of detection in homogenous clutter. Numerical experiments on simulated data are presented to validate the improved performance of the ellipse detector with respect to the ATI phase approach. Finally, the detection capability of the proposed method is demonstrated by measured SAR data.
基金supported by the National Natural Science Foundation of China(11071213,11101362)Natural Science Foundation of Zhejiang Province(R6090034)Specialized Research Foundation for the Doctor Program of Higher Education(20100101110001)
文摘In this paper,we consider the limiting spectral distribution of the information-plus-noise type sample covariance matrices Cn=1/N（Rn＋σXn）（Rn＋σXn）,under the assumption that the entries of Xn are independent but non-identically distributed random variables.It is proved that,almost surely,the empirical spectral distribution of Cn converges weakly to a non-random distribution whose Stieltjes transform satisfies a certain equation.Our result extends the previous one with the entries of Xn are i.i.d.random varibles to a more general case.The proof of the result mainly employs the Stein equation and the cumulant expansion formula of independent random variables.
文摘The performance evaluation of automatic carrier landing system(ACLS)is an important part in the field of carrier aircraft landing control.Combining grey analytic hierarchy theory and data normalization theory,an improved grey analytic hierarchy method is introduced to evaluate the performance of ACLS.A complete performance evaluation indicators system of ACLS is established,and the definition and calculation formula of each indicator are provided.The grey analytic hierarchy model is modified to improve the real-time performance of the algorithm,where traditional expert scoring sampling matrix is substituted by an indicator normalized sample matrix.Taking a certain ACLS as an example,the experimental simulation is carried out,and the simulation results verify the reliability and the accuracy of the improved grey analytic hierarchy method.
基金This study was supported by the Scientific Research Project of Hubei Provincial Department of Education(No.B2018029).
文摘In actual exploration,the demand for 3D seismic data collection is increasing,and the requirements for data are becoming higher and higher.Accordingly,the collection cost and data volume also increase.Aiming at this problem,we make use of the nature of data sparse expression,based on the theory of compressed sensing,to carry out the research on the efficient collection method of seismic data.It combines the collection of seismic data and the compression in data processing in practical work,breaking through the limitation of the traditional sampling frequency,and the sparse characteristics of the seismic signal are utilized to reconstruct the missing data.We focus on the key elements of the sampling matrix in the theory of compressed sensing,and study the methods of seismic data acquisition.According to the conditions that the compressed sensing sampling matrix needs to meet,we introduce a new random acquisition scheme,which introduces the widely used Low-density Parity-check(LDPC)sampling matrix in image processing into seismic exploration acquisition.Firstly,its properties are discussed and its conditions for satisfying the sampling matrix in compressed sensing are verified.Then the LDPC sampling method and the conventional data acquisition method are used to synthesize seismic data reconstruction experiments.The reconstruction results,signal-to-noise ratio and reconstruction error are compared to verify the seismic data based on sparse constraints.The LDPC sampling method improves the current seismic data reconstruction efficiency,reduces the exploration cost and the effectiveness and feasibility of the method.
基金supported by the National Natural Science Foundation of China (No.61302062)the National Natural Science Foundation of China (No.61571244)the Natural Science Foundation of Tianjin for Young Scientist (No.13JCQNJC00900)
文摘In order to solve the problem of high-speed sampling in OFDM based ultra wide band(UWB) systems, this paper first gives analysis on the applicability of existing compressed sampling methods. Then, on the basis of an established segmented observation model, it presents an optimized parallel segmented compressed sampling(OPSCS) scheme based on Hadamard matrix. The orthogonal Hadamard matrix is adopted to construct the segmented measurement matrix with any dimensions, thus orthogonal or quasi-orthogonal multiplex observation sequences are obtained, and the restricted isometry property is improved. The optimized orthogonal matching pursuit algorithm is also used for the known sparsity avoiding iterative operation. Researches show that the proposed method can effectively reduce the sampling rate in OFDM-UWB systems, and also has a good ability of noise resisting that it achieves a high system performance better than the existing schemes of compressed sampling and even Nyquist rate sampling.
文摘Let {vij}, i, j = 1, 2, …, be i.i.d, random variables with Ev11 = 0, Ev11^2 = 1 and a1 = （ai1,…, aiM） be random vectors with {aij} being i.i.d, random variables. Define XN =（x1,…, xk） and SN =XNXN^T,where xi=ai×si and si=1/√N（v1i,…, vN,i）^T. The spectral distribution of SN is proven to converge, with probability one, to a nonrandom distribution function under mild conditions.
文摘Wireless Communication is a system for communicating information from one point to other,without utilizing any connections like wire,cable,or other physical medium.Cognitive Radio(CR)based systems and networks are a revolutionary new perception in wireless communications.Spectrum sensing is a vital task of CR to avert destructive intrusion with licensed primary or main users and discover the accessible spectrum for the efficient utilization of the spectrum.Centralized Cooperative Spectrum Sensing(CSS)is a kind of spectrum sensing.Most of the test metrics designed till now for sensing the spectrum is produced by using the Sample Covariance Matrix(SCM)of the received signal.Some of the methods that use the SCM for the process of detection are Pietra-Ricci Index Detector(PRIDe),Hadamard Ratio(HR)detector,Gini Index Detector(GID),etc.This paper presents the simulation and comparative perfor-mance analysis of PRIDe with various other detectors like GID,HR,Arithmetic to Geometric Mean(AGM),Volume-based Detector number 1(VD1),Maximum-to-Minimum Eigenvalue Detection(MMED),and Generalized Likelihood Ratio Test(GLRT)using the MATLAB software.The PRIDe provides better performance in the presence of variations in the power of the signal and the noise power with less computational complexity.
基金Authors acknowledge support from the CHN Energy project(GJPT-20-18).
文摘After the implementation of ultra-low emission policies,the pollutant emissions from the coal-fired power generation systems in China have been further reduced,which creates more critical requirements for the control accuracies of denitrification systems using selective catalytic reduction technology and controls of ammonia slip.This article presents big data-based technologies for controlling ammonia slip,through precise ammonia injections,which were applied and demonstrated for a flue gas denitrification system of a Chinese coal-fired power plant.Through examinations and analyses of the basic operating conditions of the unit and parameters,such as NOx emission control efficiency,ammonia injection amount of the denitrification system,and non-uniformity of NOx concentrations in the denitrification zone were compared before and after the implementation of these technologies,the outcome proves that this artificial intelligence algorithm based on big data can effectively solve the automatic control problem of denitrification system under complex working conditions such as varied unit loads,day and night operation changed coal source.In addition to the effective controls of the ammonia slip of the system,the controls of NOx emission of the system become more stabilized,creating a successful example for wider applications of these precise ammonia injection control technologies in the future.Analyses show that NOx non-uniformities can be reduced by more than 50%under both stable and variable load conditions.NOx fluctuations at the unit outlet are tightly controlled within±10 mg/Nm^(3) under variable load conditions and within±5 mg/Nm^(3) under stable conditions.The average ammonia injection amounts under various load conditions have decreased by 15.7%.
