Low-frequency signals have been proven valuable in the fields of target detection and geological exploration.Nevertheless,the practical implementation of these signals is hindered by large antenna diameters,limiting t...Low-frequency signals have been proven valuable in the fields of target detection and geological exploration.Nevertheless,the practical implementation of these signals is hindered by large antenna diameters,limiting their potential applications.Therefore,it is imperative to study the creation of lowfrequency signals using antennas with suitable dimensions.In contrast to conventional mechanical antenna techniques,our study generates low-frequency signals in the spatial domain utilizing the principle of the Doppler effect.We also defines the antenna array architecture,the timing sequency,and the radiating element signal waveform,and provides experimental prototypes including 8/64 antennas based on earlier research.In the conducted experiments,121 MHz,40 MHz,and 10 kHz composite signals are generated by 156 MHz radiating element signals.The composite signal spectrum matches the simulations,proving our low-frequency signal generating method works.This holds significant implications for research on generating low-frequency signals with small-sized antennas.展开更多
The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andf...The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andfiltering is analyzed first in the paper.The advantage of adjustable time-frequency window of wavelet transform is introduced.Secondly the relationship between harmonic wavelet and multiple analytic band-pass filter is analyzed.The coherence of the multiple analytic band-pass filter and harmonic wavelet base function is discussed,and the characteristic that multiple analytic band-pass filter included in the harmonic wavelet transform is founded.Thirdly,by extending the harmonic wavelet transform,the concept of the adaptive harmonic window and its theoretical equation without decomposition are put forward in this paper.Then comparing with the Hanning window,the good performance of restraining side-lobe leakage possessed by adaptive harmonic window is shown,and the adaptive characteristics of window width changing and analytical center moving of the adaptive harmonic window are presented.Finally,the proposed adaptive harmonic window is applied to weak signal extraction and high frequency orbit extraction of high speed rotor under strong noise,and the satisfactory results are achieved.The application results show that the adaptive harmonic window function can be successfully applied to the actual engineering signal processing.展开更多
DQPSK modem has been chosen as the modem scheme in many mobile communication systems. A new signal processing technique of π/4-DQPSK modem based on software radio is discussed in this paper. Unlike many other softwar...DQPSK modem has been chosen as the modem scheme in many mobile communication systems. A new signal processing technique of π/4-DQPSK modem based on software radio is discussed in this paper. Unlike many other software radio solutions to the subject, we choose a universal digital radio baseband processor operating as the co-processor of DSP. Only the core algorithms for signal processing are implemented with DSP. Thus the computation burden on DSP is reduced significantly. Compared with the traditional ones, the technique mentioned in this paper is more promising and attractive. It is extremely compact and power-efficient, which is often required by a mobile communication system. The implementation of baseband signal processing for π/4-DQPSK modem on this platform is illustrated in detail. Special emphases are laid on the architecture of the system and the algorithms used in the baseband signal processing. Finally, some experimental results are presented and the performances of the signal processing and compensation algorithms are evaluated through computer simulations.展开更多
The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and ...The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.展开更多
This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter mod...This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.展开更多
The investigation of novel signal processing tools is one of the hottest research topics in modern signal processing community. Among them, the algebraic and geometric signal processing methods are the most powerful t...The investigation of novel signal processing tools is one of the hottest research topics in modern signal processing community. Among them, the algebraic and geometric signal processing methods are the most powerful tools for the representation of the classical signal processing method. In this paper, we provide an overview of recent contributions to the algebraic and geometric signal processing. Specifically, the paper focuses on the mathematical structures behind the signal processing by emphasizing the algebraic and geometric structure of signal processing. The two major topics are discussed. First, the classical signal processing concepts are related to the algebraic structures, and the recent results associated with the algebraic signal processing theory are introduced. Second, the recent progress of the geometric signal and information processing representations associated with the geometric structure are discussed. From these discussions, it is concluded that the research on the algebraic and geometric structure of signal processing can help the researchers to understand the signal processing tools deeply, and also help us to find novel signal processing methods in signal processing community. Its practical applications are expected to grow significantly in years to come, given that the algebraic and geometric structure of signal processing offer many advantages over the traditional signal processing.展开更多
In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristi...In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.展开更多
Due to the heavy congestion in HF bands, HF radars are restricted to operating within narrow frequency bands. To improve the system bandwidth and avoid heavy interference bands, a quasi-random step frequency signal wi...Due to the heavy congestion in HF bands, HF radars are restricted to operating within narrow frequency bands. To improve the system bandwidth and avoid heavy interference bands, a quasi-random step frequency signal with discontinuous bands is presented. A novel two-dimensional signal processing scheme for this signal is proposed on the basis of delicate signal analysis. Simulation results demonstrate that the scheme could successfully realize the resolutions by decoupling the range-Doppler ambiguity, and effectively suppress the maximal sidelobe. Moreover, the scheme is simple and has good numerical stability.展开更多
The work principle of all fiber optical current transducer (AFOCT) was introduced. By analyzing the characteristic of photo-detector's output, a measurement and signal processing scheme based on sine wave modulati...The work principle of all fiber optical current transducer (AFOCT) was introduced. By analyzing the characteristic of photo-detector's output, a measurement and signal processing scheme based on sine wave modulation and demodulation was put forward for eliminating the influence of light intensity change and modulation degree change. A digital signal processing system and a calibration scheme were also advanced. The experimental data show that the mean ratio error is 0.016 74% for direct current and 0.035% for alternating current, and the correlation coefficient of linearity is up to 0.999 982 4, meeting the precision requirement of 0.2 grade. Stability experiments and temperature drift experiments show the AFOCT has a better stable capability.展开更多
Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity ...Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.展开更多
The problem of adaptive detection in the situation of signal mismatch is considered; that is, the actual signal steering vector is not aligned with the nominal one. Two novel tunable detectors are proposed. They can c...The problem of adaptive detection in the situation of signal mismatch is considered; that is, the actual signal steering vector is not aligned with the nominal one. Two novel tunable detectors are proposed. They can control the degree to which the mismatched signals are rejected. Remarkably, it is found that they both cover existing famous detectors as their special cases. More importantly, they possess the constant false alarm rate（CFAR）property and achieve enhanced mismatched signal rejection or improved robustness than their natural competitors. Besides, they can provide slightly better matched signals detection performance than the existing detectors.展开更多
Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms us...Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms usually perform low accuracy.In this work,a sparsity adaptive signal reconstruction algorithm using sensing dictionary is proposed to achieve a lower reconstruction error.The sparsity estimation method is combined with the construction of the support set based on sensing dictionary.Using the adaptive sparsity method,an iterative signal reconstruction algorithm is proposed.The sufficient conditions for the exact signal reconstruction of the algorithm also is proved by theory.According to a series of simulations,the results show that the proposed method has higher precision compared with other state-of-the-art signal reconstruction algorithms especially in a high compression ratio scenarios.展开更多
An input-output signal selection based on Phillips-Heffron model of a parallel high voltage alternative current/high voltage direct current(HVAC/HVDC) power system is presented to study power system stability. It is w...An input-output signal selection based on Phillips-Heffron model of a parallel high voltage alternative current/high voltage direct current(HVAC/HVDC) power system is presented to study power system stability. It is well known that appropriate coupling of inputs-outputs signals in the multivariable HVDC-HVAC system can improve the performance of designed supplemetary controller. In this work, different analysis techniques are used to measure controllability and observability of electromechanical oscillation mode. Also inputs–outputs interactions are considered and suggestions are drawn to select the best signal pair through the system inputs-outputs. In addition, a supplementary online adaptive controller for nonlinear HVDC to damp low frequency oscillations in a weakly connected system is proposed. The results obtained using MATLAB software show that the best output-input for damping controller design is rotor speed deviation as out put and phase angle of rectifier as in put. Also response of system equipped with adaptive damping controller based on HVDC system has appropriate performance when it is faced with faults and disturbance.展开更多
An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode ...An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.展开更多
According to the features of the wideband underwater acoustic signals,an algorithm for the wideband ambiguity function is put forward based on Mellin transform.The wideband acoustic signal processing using the fast Me...According to the features of the wideband underwater acoustic signals,an algorithm for the wideband ambiguity function is put forward based on Mellin transform.The wideband acoustic signal processing using the fast Mellin transform is also explored.The theoretical analysis and simulation results show that the algorithm has not only high computation efficiency but also good concentration in wideband ambiguity domain.It suits for the wideband underwater acoustic signal processing.展开更多
This paper simply discusses the outer channels and their characteristics of information communication between the fuze and outer environments based on the view that the fuze is an information system, and deeply analyz...This paper simply discusses the outer channels and their characteristics of information communication between the fuze and outer environments based on the view that the fuze is an information system, and deeply analyzes the information features of high frequency signal processing that mainly recovers the echo signals and controls the noises instead of picking up the required target information. But it can reduce the uncertainty of the signal caused by noise. The information processing of fuze is mainly completed by the low frequency information processing system.展开更多
In order to realize the real-time and precise test for a weapon system of a certain type of fighter,a signal classification method according to attributes is proposed,common input channels for multiple signals are con...In order to realize the real-time and precise test for a weapon system of a certain type of fighter,a signal classification method according to attributes is proposed,common input channels for multiple signals are configured optimally,and a test adapter and an adaptive signal conditioning module is designed. The hardware of conditioning module can be configured flexibly and the programmable test range can be adjusted owing to programmable multiplexer. An FPGA adaptive filter is designed by the calculated filter coefficient vectors with LMS method to solve the problem of parallel test of fighter weapon system in electromagnetic interference environment. The adaptive signal conditioning technology is characterized by high efficiency,precision and integration. Its application makes the test system successful to conduct real-time and parallel test for a weapon system,which is developed based on VXI bus and virtual-instrument technology.展开更多
This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, ...This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, the binary tree search,and the residual monitoring mechanism, two adaptive block greedy algorithms are proposed to achieve a high probability adaptive reconstruction. The use of the block sparsity can greatly improve the efficiency of the support selection and reduce the lower boundary of the sub-sampling rate. Furthermore, the addition of binary tree search and monitoring mechanism with two different supports self-adaption methods overcome the instability caused by the fixed block length while optimizing the recovery of the unknown signal.The simulations and analysis of the adaptive reconstruction ability and theoretical computational complexity are given. Also, we verify the feasibility and effectiveness of the two algorithms by the experiments of receiving multi-narrowband signals on an analogto-information converter(AIC). Finally, an optimum reconstruction characteristic of two algorithms is found to facilitate efficient reception in practical applications.展开更多
雷达、声呐和无线通信等应用对于自适应波束形成的抗干扰能力和实时性提出了更高的要求。传统基于最速迭代的自适应波束形成算法存在“过拟合”特性,导致在相干干扰条件下的干扰抑制性能急剧下降。另外,当干扰存在扰动且导向向量失配时...雷达、声呐和无线通信等应用对于自适应波束形成的抗干扰能力和实时性提出了更高的要求。传统基于最速迭代的自适应波束形成算法存在“过拟合”特性,导致在相干干扰条件下的干扰抑制性能急剧下降。另外,当干扰存在扰动且导向向量失配时,也无法有效抑制干扰。针对上述问题,本文提出了一种基于共轭梯度(Conjugate Gradient,CG)加速的二次约束宽零陷干扰抑制自适应波束形成方法。该方法首先利用CG算法的快速收敛特性,完成采样协方差矩阵与导向向量间线性方程组的求解;其次将CG算法输出的权矢量作为迭代最速波束形成方法的初始权值,利用该方法的“过拟合”特性,确保对期望信号的强锁定;最后提出了一种强化干扰特征的波达方向(Direction of Arrival,DOA)估计方法,实现宽带相干干扰下的干扰来波方向估计,并将该方法与二次约束零陷展宽方法结合,用于捕获干扰特征,形成自适应零陷。仿真实验验证了所提方法在单快拍、宽带相干干扰条件下,能够自适应抑制干扰且稳健性较好。展开更多
基金Science and Technology Project of Aerospace Information Research Institute,Chinese Academy of Sciences(Y910340Z2F)Science and Technology Project of BBEF(E3E2010201)。
文摘Low-frequency signals have been proven valuable in the fields of target detection and geological exploration.Nevertheless,the practical implementation of these signals is hindered by large antenna diameters,limiting their potential applications.Therefore,it is imperative to study the creation of lowfrequency signals using antennas with suitable dimensions.In contrast to conventional mechanical antenna techniques,our study generates low-frequency signals in the spatial domain utilizing the principle of the Doppler effect.We also defines the antenna array architecture,the timing sequency,and the radiating element signal waveform,and provides experimental prototypes including 8/64 antennas based on earlier research.In the conducted experiments,121 MHz,40 MHz,and 10 kHz composite signals are generated by 156 MHz radiating element signals.The composite signal spectrum matches the simulations,proving our low-frequency signal generating method works.This holds significant implications for research on generating low-frequency signals with small-sized antennas.
基金Project(51675262)supported by the National Natural Science Foundation of ChinaProject(6140210020102)supported by the Advance Research Field Fund Project of ChinaProject(2016YFD0700800)supported by the National Key Research and Development Plan of China
文摘The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andfiltering is analyzed first in the paper.The advantage of adjustable time-frequency window of wavelet transform is introduced.Secondly the relationship between harmonic wavelet and multiple analytic band-pass filter is analyzed.The coherence of the multiple analytic band-pass filter and harmonic wavelet base function is discussed,and the characteristic that multiple analytic band-pass filter included in the harmonic wavelet transform is founded.Thirdly,by extending the harmonic wavelet transform,the concept of the adaptive harmonic window and its theoretical equation without decomposition are put forward in this paper.Then comparing with the Hanning window,the good performance of restraining side-lobe leakage possessed by adaptive harmonic window is shown,and the adaptive characteristics of window width changing and analytical center moving of the adaptive harmonic window are presented.Finally,the proposed adaptive harmonic window is applied to weak signal extraction and high frequency orbit extraction of high speed rotor under strong noise,and the satisfactory results are achieved.The application results show that the adaptive harmonic window function can be successfully applied to the actual engineering signal processing.
文摘DQPSK modem has been chosen as the modem scheme in many mobile communication systems. A new signal processing technique of π/4-DQPSK modem based on software radio is discussed in this paper. Unlike many other software radio solutions to the subject, we choose a universal digital radio baseband processor operating as the co-processor of DSP. Only the core algorithms for signal processing are implemented with DSP. Thus the computation burden on DSP is reduced significantly. Compared with the traditional ones, the technique mentioned in this paper is more promising and attractive. It is extremely compact and power-efficient, which is often required by a mobile communication system. The implementation of baseband signal processing for π/4-DQPSK modem on this platform is illustrated in detail. Special emphases are laid on the architecture of the system and the algorithms used in the baseband signal processing. Finally, some experimental results are presented and the performances of the signal processing and compensation algorithms are evaluated through computer simulations.
基金Supported by National Science and Technology Support Program(2014BAD06B04-1-09)China Postdoctoral Fund(2016M601406)Heilongjiang Postdoctoral Fund(LBHZ15024)
文摘The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.
基金supported by the National Natural Science Foundation of China(60901056)
文摘This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.
基金Sponsored by Program for Changjiang Scholars and Innovative Research Team in University ( IRT1005 )the National Natural Science Founda-tions of China ( 61171195 and 61179031)Program for New Century Excellent Talents in University ( NCET-12-0042)
文摘The investigation of novel signal processing tools is one of the hottest research topics in modern signal processing community. Among them, the algebraic and geometric signal processing methods are the most powerful tools for the representation of the classical signal processing method. In this paper, we provide an overview of recent contributions to the algebraic and geometric signal processing. Specifically, the paper focuses on the mathematical structures behind the signal processing by emphasizing the algebraic and geometric structure of signal processing. The two major topics are discussed. First, the classical signal processing concepts are related to the algebraic structures, and the recent results associated with the algebraic signal processing theory are introduced. Second, the recent progress of the geometric signal and information processing representations associated with the geometric structure are discussed. From these discussions, it is concluded that the research on the algebraic and geometric structure of signal processing can help the researchers to understand the signal processing tools deeply, and also help us to find novel signal processing methods in signal processing community. Its practical applications are expected to grow significantly in years to come, given that the algebraic and geometric structure of signal processing offer many advantages over the traditional signal processing.
文摘In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.
文摘Due to the heavy congestion in HF bands, HF radars are restricted to operating within narrow frequency bands. To improve the system bandwidth and avoid heavy interference bands, a quasi-random step frequency signal with discontinuous bands is presented. A novel two-dimensional signal processing scheme for this signal is proposed on the basis of delicate signal analysis. Simulation results demonstrate that the scheme could successfully realize the resolutions by decoupling the range-Doppler ambiguity, and effectively suppress the maximal sidelobe. Moreover, the scheme is simple and has good numerical stability.
文摘The work principle of all fiber optical current transducer (AFOCT) was introduced. By analyzing the characteristic of photo-detector's output, a measurement and signal processing scheme based on sine wave modulation and demodulation was put forward for eliminating the influence of light intensity change and modulation degree change. A digital signal processing system and a calibration scheme were also advanced. The experimental data show that the mean ratio error is 0.016 74% for direct current and 0.035% for alternating current, and the correlation coefficient of linearity is up to 0.999 982 4, meeting the precision requirement of 0.2 grade. Stability experiments and temperature drift experiments show the AFOCT has a better stable capability.
基金The authors gratefully acknowledge the support of the National Natural Science Foundation of China(No.11574250).
文摘Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.
基金supported by the National Natural Science Foundation of China(6110216960925005)
文摘The problem of adaptive detection in the situation of signal mismatch is considered; that is, the actual signal steering vector is not aligned with the nominal one. Two novel tunable detectors are proposed. They can control the degree to which the mismatched signals are rejected. Remarkably, it is found that they both cover existing famous detectors as their special cases. More importantly, they possess the constant false alarm rate（CFAR）property and achieve enhanced mismatched signal rejection or improved robustness than their natural competitors. Besides, they can provide slightly better matched signals detection performance than the existing detectors.
基金supported by the National Natural Science Foundation of China(61773202,71874081)the Special Financial Grant from China Postdoctoral Science Foundation(2017T100366)+2 种基金the Key Laboratory of Avionics System Integrated Technology for National Defense Science and Technology,China Institute of Avionics Radio Electronics(6142505180407)the Open Fund of CAAC Key laboratory of General Aviation Operation,Civil Aviation Management Institute of China(CAMICKFJJ-2019-04)the Innovation Project of the Civil Aviation Administration of China(EAB19001)。
文摘Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms usually perform low accuracy.In this work,a sparsity adaptive signal reconstruction algorithm using sensing dictionary is proposed to achieve a lower reconstruction error.The sparsity estimation method is combined with the construction of the support set based on sensing dictionary.Using the adaptive sparsity method,an iterative signal reconstruction algorithm is proposed.The sufficient conditions for the exact signal reconstruction of the algorithm also is proved by theory.According to a series of simulations,the results show that the proposed method has higher precision compared with other state-of-the-art signal reconstruction algorithms especially in a high compression ratio scenarios.
文摘An input-output signal selection based on Phillips-Heffron model of a parallel high voltage alternative current/high voltage direct current(HVAC/HVDC) power system is presented to study power system stability. It is well known that appropriate coupling of inputs-outputs signals in the multivariable HVDC-HVAC system can improve the performance of designed supplemetary controller. In this work, different analysis techniques are used to measure controllability and observability of electromechanical oscillation mode. Also inputs–outputs interactions are considered and suggestions are drawn to select the best signal pair through the system inputs-outputs. In addition, a supplementary online adaptive controller for nonlinear HVDC to damp low frequency oscillations in a weakly connected system is proposed. The results obtained using MATLAB software show that the best output-input for damping controller design is rotor speed deviation as out put and phase angle of rectifier as in put. Also response of system equipped with adaptive damping controller based on HVDC system has appropriate performance when it is faced with faults and disturbance.
基金Project(61573381)supported by the National Natural Science Foundation of ChinaProject(2012AA051601)supported by the National High-tech Research and Development Program of China
文摘An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.
基金Sponsored by National Nature Science Foundation of China(10474079)
文摘According to the features of the wideband underwater acoustic signals,an algorithm for the wideband ambiguity function is put forward based on Mellin transform.The wideband acoustic signal processing using the fast Mellin transform is also explored.The theoretical analysis and simulation results show that the algorithm has not only high computation efficiency but also good concentration in wideband ambiguity domain.It suits for the wideband underwater acoustic signal processing.
文摘This paper simply discusses the outer channels and their characteristics of information communication between the fuze and outer environments based on the view that the fuze is an information system, and deeply analyzes the information features of high frequency signal processing that mainly recovers the echo signals and controls the noises instead of picking up the required target information. But it can reduce the uncertainty of the signal caused by noise. The information processing of fuze is mainly completed by the low frequency information processing system.
基金Sponsored by the Key Equipment Research Project of Air Force of China (KJZ06119)
文摘In order to realize the real-time and precise test for a weapon system of a certain type of fighter,a signal classification method according to attributes is proposed,common input channels for multiple signals are configured optimally,and a test adapter and an adaptive signal conditioning module is designed. The hardware of conditioning module can be configured flexibly and the programmable test range can be adjusted owing to programmable multiplexer. An FPGA adaptive filter is designed by the calculated filter coefficient vectors with LMS method to solve the problem of parallel test of fighter weapon system in electromagnetic interference environment. The adaptive signal conditioning technology is characterized by high efficiency,precision and integration. Its application makes the test system successful to conduct real-time and parallel test for a weapon system,which is developed based on VXI bus and virtual-instrument technology.
基金supported by the National Natural Science Foundation of China(61172159)
文摘This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, the binary tree search,and the residual monitoring mechanism, two adaptive block greedy algorithms are proposed to achieve a high probability adaptive reconstruction. The use of the block sparsity can greatly improve the efficiency of the support selection and reduce the lower boundary of the sub-sampling rate. Furthermore, the addition of binary tree search and monitoring mechanism with two different supports self-adaption methods overcome the instability caused by the fixed block length while optimizing the recovery of the unknown signal.The simulations and analysis of the adaptive reconstruction ability and theoretical computational complexity are given. Also, we verify the feasibility and effectiveness of the two algorithms by the experiments of receiving multi-narrowband signals on an analogto-information converter(AIC). Finally, an optimum reconstruction characteristic of two algorithms is found to facilitate efficient reception in practical applications.
文摘雷达、声呐和无线通信等应用对于自适应波束形成的抗干扰能力和实时性提出了更高的要求。传统基于最速迭代的自适应波束形成算法存在“过拟合”特性,导致在相干干扰条件下的干扰抑制性能急剧下降。另外,当干扰存在扰动且导向向量失配时,也无法有效抑制干扰。针对上述问题,本文提出了一种基于共轭梯度(Conjugate Gradient,CG)加速的二次约束宽零陷干扰抑制自适应波束形成方法。该方法首先利用CG算法的快速收敛特性,完成采样协方差矩阵与导向向量间线性方程组的求解;其次将CG算法输出的权矢量作为迭代最速波束形成方法的初始权值,利用该方法的“过拟合”特性,确保对期望信号的强锁定;最后提出了一种强化干扰特征的波达方向(Direction of Arrival,DOA)估计方法,实现宽带相干干扰下的干扰来波方向估计,并将该方法与二次约束零陷展宽方法结合,用于捕获干扰特征,形成自适应零陷。仿真实验验证了所提方法在单快拍、宽带相干干扰条件下,能够自适应抑制干扰且稳健性较好。
