A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer syste...A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.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 addresses the problem of adaptively estimating the consistent parameters for non Gaussian nonminimum MA processes with symmetric PDF using the fourth order cumulant of the underlying processes. The process...This paper addresses the problem of adaptively estimating the consistent parameters for non Gaussian nonminimum MA processes with symmetric PDF using the fourth order cumulant of the underlying processes. The processes may be corrupted by additive noise.展开更多
It is required in the diagonally loaded robust adaptive beamforming the automatic determination of the loading level which is practically a challenging problem.A constant modulus restoral method is herein presented to...It is required in the diagonally loaded robust adaptive beamforming the automatic determination of the loading level which is practically a challenging problem.A constant modulus restoral method is herein presented to choose the diagonal loading level adaptively for the extraction of a desired signal with constant modulus(a common feature of the phase modulation signals).By introducing the temporal smoothing technique,the proposed constant modulus restoral diagonally loaded robust adaptive beamformer provides increased capability compared with some existing robust adaptive beamformers in rejecting interferences and noise while protecting the signal-of-interest.Simulation results are included to illustrate the performance of the proposed beamformer.展开更多
A new algorithm, called the adaptive exponent smoothing gradient algorithm (AESGA), is developed from Widrow′s LMS algorithm. It is based on the fact that LMS algorithm has properties of time delaying and low pass ...A new algorithm, called the adaptive exponent smoothing gradient algorithm (AESGA), is developed from Widrow′s LMS algorithm. It is based on the fact that LMS algorithm has properties of time delaying and low pass filtering. This paper shows that the algorithm, on the domain of {Ω 1:α∈(0,1)}×{Ω 2:β(0,∞)} , unbiasedly and asymptotically converges to the Winner solution when the signal is a stationary Gauss stochastic process. The convergent property and the performance misadjustment are analyzed in theory. And calculation method of the algorithm is also suggested. Numerical results given by computer simulations show that the algorithm is effective.展开更多
In this paper, a novel DOA estimation methodology based upon the technology of adaptive nulling antenna is proposed. Initially, the nulling antenna obtains the weight vector by LMS algorithm and power inversion criter...In this paper, a novel DOA estimation methodology based upon the technology of adaptive nulling antenna is proposed. Initially, the nulling antenna obtains the weight vector by LMS algorithm and power inversion criterion.Afterwards, reciprocal of the antenna pattern is defined as the spatial spectrum and the extracted peak values are corresponded to the estimated DOA. Through observation of the spectrum and data analysis of variable steps and SNRs, the simulation results demonstrate that the proposed method can estimate DOA above board. Furthermore, the estimation error of the proposed technique is directly proportional to step size and is inversely proportional to SNR. Unlike the existing MUSIC algorithm, the proposed algorithm has less computational complexity as it eliminates the need of estimating the number of signals and the eigenvalue decomposition of covariance matrix. Also it outperforms MUSIC algorithm, the recently proposed MUSIC-Like algorithm and classical methods by achieving better resolution with narrow width of peaks.展开更多
To improve the identification capability of AP algorithm in time-varying sparse system, we propose a block parallel l_0-SWL-DCD-AP algorithm in this paper. In the proposed algorithm, we first introduce the l_0-norm co...To improve the identification capability of AP algorithm in time-varying sparse system, we propose a block parallel l_0-SWL-DCD-AP algorithm in this paper. In the proposed algorithm, we first introduce the l_0-norm constraint to promote its application for sparse system. Second, we use the shrinkage denoising method to improve its track ability. Third, we adopt the widely linear processing to take advantage of the non-circular properties of communication signals. Last, to reduce the high computational complexity and make it easy to implemented, we utilize the dichotomous coordinate descent(DCD) iterations and the parallel processing to deal with the tapweight update in the proposed algorithm. To verify the convergence condition of the proposed algorithm, we also analyze its steadystate behavior. Several simulation are done and results show that the proposed algorithm can achieve a faster convergence speed and a lower steady-state misalignment than similar APA-type algorithm. When apply the proposed algorithm in the decision feedback equalizer(DFE), the bite error rate(BER) decreases obviously.展开更多
Although a various of existing techniques are able to improve the performance of detection of the weak interesting sig- nal, how to adaptively and efficiently attenuate the intricate noises especially in the case of n...Although a various of existing techniques are able to improve the performance of detection of the weak interesting sig- nal, how to adaptively and efficiently attenuate the intricate noises especially in the case of no available reference noise signal is still the bottleneck to be overcome. According to the characteristics of sonar arrays, a multi-channel differencing method is presented to provide the prerequisite reference noise. However, the ingre- dient of obtained reference noise is too complicated to be used to effectively reduce the interference noise only using the clas- sical linear cancellation methods. Hence, a novel adaptive noise cancellation method based on the multi-kernel normalized least- mean-square algorithm consisting of weighted linear and Gaussian kernel functions is proposed, which allows to simultaneously con- sider the cancellation of linear and nonlinear components in the reference noise. The simulation results demonstrate that the out- put signal-to-noise ratio （SNR） of the novel multi-kernel adaptive filtering method outperforms the conventional linear normalized least-mean-square method and the mono-kernel normalized least- mean-square method using the realistic noise data measured in the lake experiment.展开更多
The proposed blind adaptive multiuser detector utilizes the signature waveform and time information of the desired user. With each received sample vector, the proposed algorithm updates the detector and gives the symb...The proposed blind adaptive multiuser detector utilizes the signature waveform and time information of the desired user. With each received sample vector, the proposed algorithm updates the detector and gives the symbol estimate in the current time slot. Such property facilitates it to track time-varying channels.展开更多
To cope with the time-varying and Dopper-broadened clutter in airborne phase array radars, it is required that the signal processing should be adaptive and two-dimensional both in time and in space. However, the optim...To cope with the time-varying and Dopper-broadened clutter in airborne phase array radars, it is required that the signal processing should be adaptive and two-dimensional both in time and in space. However, the optimum two-dimensional adaptive processing is hard to realize real-timely because it requires a large amount of computation. From the idea of approximating the clutter process by using an auto regressive process, a linear prediction approach is proposed to realize the adaptive space-time processing of airborne adaptive array signals. The research shows that the clutter process can be well approximated by a low-order AR process, so a low-order linear prediction receiver can get a sub-optimum performance at a very low expense. Besides, the low-order linear prediction receiver has additional degrees of freedom to cope with other colored noises and interferences. In consideration of the many advantages of the linear prediction receiver in both algorithms and realizations, it has a good prospect in its application to air borne adaptive array signal processing.展开更多
The paper analyses the characteristics of radio frequency interference （RFI） in HF surface wave radar （HFSWR） which adopts the linear frequency modulated interrupted continuous wave （FMICW）. RFI will influence a...The paper analyses the characteristics of radio frequency interference （RFI） in HF surface wave radar （HFSWR） which adopts the linear frequency modulated interrupted continuous wave （FMICW）. RFI will influence all the range cells including all the positive frequency and negative frequency, and the negative frequency range cells contain only the interference information. Based on the above characteristics, we introduce and analyze a new adaptive interference mitigation beamforming algorithm using the negative frequency range cells samples to estimate the interference covariance matrix. Experimental results confirm that this general and robust algorithm can achieve effective RFI suppression using the data recorded by the HFSWR, located near Zhoushan in Zhejiang China.展开更多
An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packe...An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packet theory to adaptive beamforming, a wavelet packet transform-based adaptive beamforming algorithm (WP-ABF) is proposed . This WP-ABF algorithm uses wavelet packet transform as the preprocessing, and the wavelet packet transformed signal uses least mean square algorithm to implement the ~adaptive beamforming. White noise can be wiped off under wavelet packet transform according to the different characteristics of signal and white under the wavelet packet transform. Theoretical analysis and simulations demonstrate that the proposed WP-ABF algorithm converges faster than the conventional adaptive beamforming algorithm and the wavelet transform-based beamforming algorithm. Simulation results also reveal that the convergence of the algorithm relates closely to the wavelet base and series; that is, the algorithm convergence gets better with the increasing of series, and for the same series of wavelet base the convergence gets better with the increasing of regularity.展开更多
This work describes a novel adaptive matrix/vector gradient (AMVG) algorithm for design of IIR filters and ARMA signal models. The AMVG algorithm can track to IIR filters and ARMA systems having poles also outside the...This work describes a novel adaptive matrix/vector gradient (AMVG) algorithm for design of IIR filters and ARMA signal models. The AMVG algorithm can track to IIR filters and ARMA systems having poles also outside the unit circle. The time reversed filtering procedure was used to treat the unstable conditions. The SVD-based null space solution was used for the initialization of the AMVG algorithm. We demonstrate the feasibility of the method by designing a digital phase shifter, which adapts to complex frequency carriers in the presence of noise. We implement the half-sample delay filter and describe the envelope detector based on the Hilbert transform filter.展开更多
Noise cancellation is very important in the field of signal processing. Inthis paper, the designation of a modified LMS Adaptive Noise Cancellation is demonstrated in detail;the model is simulated. We have compared th...Noise cancellation is very important in the field of signal processing. Inthis paper, the designation of a modified LMS Adaptive Noise Cancellation is demonstrated in detail;the model is simulated. We have compared the performance of the new model with the old model. Theresult of the experiments shows that this designation improves the noise cancellation's performancegreatly.展开更多
The development of automation industry is inseparable from the progress of sensing technology.As a promising self-powered sensing technology,the durability and stability of triboelectric sensor(TES)have always been in...The development of automation industry is inseparable from the progress of sensing technology.As a promising self-powered sensing technology,the durability and stability of triboelectric sensor(TES)have always been inevitable challenges.Herein,a continuous charge supplement(CCS)strategy and an adaptive signal processing(ASP)method are proposed to improve the lifetime and robustness of TES.The CCS uses low friction brushes to increase the surface charge density of the dielectric,ensuring the reliability of sensing.A triboelectric mechanical motion sensor(TMMS)with CCS is designed,and its electrical signal is hardly attenuated after 1.5 million cycles after reasonable parameter optimization,which is unprecedented in linear TESs.After that,the dynamic characteristics of the CCS-TMMS are analyzed with error rates of less than 1%and 2%for displacement and velocity,respectively,and a signal-to-noise ratio of more than 35 dB.Also,the ASP used a signal conditioning circuit for impedance matching and analog-to-digital conversion to achieve a stable output of digital signals,while the integrated design and manufacture of each hardware module is achieved.Finally,an intelligent logistics transmission system(ILTS)capable of wirelessly monitoring multiple motion parameters is developed.This work is expected to contribute to automation industries such as smart factories and unmanned warehousing.展开更多
文摘A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.
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.
文摘This paper addresses the problem of adaptively estimating the consistent parameters for non Gaussian nonminimum MA processes with symmetric PDF using the fourth order cumulant of the underlying processes. The processes may be corrupted by additive noise.
基金Supported by the National Natural Science Foundation of China(No.61490691,61331019)
文摘It is required in the diagonally loaded robust adaptive beamforming the automatic determination of the loading level which is practically a challenging problem.A constant modulus restoral method is herein presented to choose the diagonal loading level adaptively for the extraction of a desired signal with constant modulus(a common feature of the phase modulation signals).By introducing the temporal smoothing technique,the proposed constant modulus restoral diagonally loaded robust adaptive beamformer provides increased capability compared with some existing robust adaptive beamformers in rejecting interferences and noise while protecting the signal-of-interest.Simulation results are included to illustrate the performance of the proposed beamformer.
文摘A new algorithm, called the adaptive exponent smoothing gradient algorithm (AESGA), is developed from Widrow′s LMS algorithm. It is based on the fact that LMS algorithm has properties of time delaying and low pass filtering. This paper shows that the algorithm, on the domain of {Ω 1:α∈(0,1)}×{Ω 2:β(0,∞)} , unbiasedly and asymptotically converges to the Winner solution when the signal is a stationary Gauss stochastic process. The convergent property and the performance misadjustment are analyzed in theory. And calculation method of the algorithm is also suggested. Numerical results given by computer simulations show that the algorithm is effective.
基金support of the Science and Technology Commission of Chongqing through the Nature Science Fund (2013jj B40005)supported by the Fundamental Research Funds for the Central University (106112016CDJZR165508) of China
文摘In this paper, a novel DOA estimation methodology based upon the technology of adaptive nulling antenna is proposed. Initially, the nulling antenna obtains the weight vector by LMS algorithm and power inversion criterion.Afterwards, reciprocal of the antenna pattern is defined as the spatial spectrum and the extracted peak values are corresponded to the estimated DOA. Through observation of the spectrum and data analysis of variable steps and SNRs, the simulation results demonstrate that the proposed method can estimate DOA above board. Furthermore, the estimation error of the proposed technique is directly proportional to step size and is inversely proportional to SNR. Unlike the existing MUSIC algorithm, the proposed algorithm has less computational complexity as it eliminates the need of estimating the number of signals and the eigenvalue decomposition of covariance matrix. Also it outperforms MUSIC algorithm, the recently proposed MUSIC-Like algorithm and classical methods by achieving better resolution with narrow width of peaks.
基金supported by the National Natural Science Foundation of China (Grant No. 61471138, 50909029 and 61531012)Program of International S\&T Cooperation (Grant No. 2013DFR20050)+1 种基金the Defense Industrial Technology Development Program (Grant No. B2420132004)the Acoustic Science and Technology Laboratory (2014)
文摘To improve the identification capability of AP algorithm in time-varying sparse system, we propose a block parallel l_0-SWL-DCD-AP algorithm in this paper. In the proposed algorithm, we first introduce the l_0-norm constraint to promote its application for sparse system. Second, we use the shrinkage denoising method to improve its track ability. Third, we adopt the widely linear processing to take advantage of the non-circular properties of communication signals. Last, to reduce the high computational complexity and make it easy to implemented, we utilize the dichotomous coordinate descent(DCD) iterations and the parallel processing to deal with the tapweight update in the proposed algorithm. To verify the convergence condition of the proposed algorithm, we also analyze its steadystate behavior. Several simulation are done and results show that the proposed algorithm can achieve a faster convergence speed and a lower steady-state misalignment than similar APA-type algorithm. When apply the proposed algorithm in the decision feedback equalizer(DFE), the bite error rate(BER) decreases obviously.
基金supported by the National Natural Science Foundation of China(6100115361271415)+2 种基金the Opening Research Foundation of State Key Laboratory of Underwater Information Processing and Control(9140C231002130C23085)the Fundamental Research Funds for the Central Universities(3102014JCQ010103102014ZD0041)
文摘Although a various of existing techniques are able to improve the performance of detection of the weak interesting sig- nal, how to adaptively and efficiently attenuate the intricate noises especially in the case of no available reference noise signal is still the bottleneck to be overcome. According to the characteristics of sonar arrays, a multi-channel differencing method is presented to provide the prerequisite reference noise. However, the ingre- dient of obtained reference noise is too complicated to be used to effectively reduce the interference noise only using the clas- sical linear cancellation methods. Hence, a novel adaptive noise cancellation method based on the multi-kernel normalized least- mean-square algorithm consisting of weighted linear and Gaussian kernel functions is proposed, which allows to simultaneously con- sider the cancellation of linear and nonlinear components in the reference noise. The simulation results demonstrate that the out- put signal-to-noise ratio （SNR） of the novel multi-kernel adaptive filtering method outperforms the conventional linear normalized least-mean-square method and the mono-kernel normalized least- mean-square method using the realistic noise data measured in the lake experiment.
基金the National Natural Science Foundation of China(No.60072048)and Natural Science Found of Guangdong Province(No.31390)
文摘The proposed blind adaptive multiuser detector utilizes the signature waveform and time information of the desired user. With each received sample vector, the proposed algorithm updates the detector and gives the symbol estimate in the current time slot. Such property facilitates it to track time-varying channels.
文摘To cope with the time-varying and Dopper-broadened clutter in airborne phase array radars, it is required that the signal processing should be adaptive and two-dimensional both in time and in space. However, the optimum two-dimensional adaptive processing is hard to realize real-timely because it requires a large amount of computation. From the idea of approximating the clutter process by using an auto regressive process, a linear prediction approach is proposed to realize the adaptive space-time processing of airborne adaptive array signals. The research shows that the clutter process can be well approximated by a low-order AR process, so a low-order linear prediction receiver can get a sub-optimum performance at a very low expense. Besides, the low-order linear prediction receiver has additional degrees of freedom to cope with other colored noises and interferences. In consideration of the many advantages of the linear prediction receiver in both algorithms and realizations, it has a good prospect in its application to air borne adaptive array signal processing.
文摘The paper analyses the characteristics of radio frequency interference （RFI） in HF surface wave radar （HFSWR） which adopts the linear frequency modulated interrupted continuous wave （FMICW）. RFI will influence all the range cells including all the positive frequency and negative frequency, and the negative frequency range cells contain only the interference information. Based on the above characteristics, we introduce and analyze a new adaptive interference mitigation beamforming algorithm using the negative frequency range cells samples to estimate the interference covariance matrix. Experimental results confirm that this general and robust algorithm can achieve effective RFI suppression using the data recorded by the HFSWR, located near Zhoushan in Zhejiang China.
文摘An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packet theory to adaptive beamforming, a wavelet packet transform-based adaptive beamforming algorithm (WP-ABF) is proposed . This WP-ABF algorithm uses wavelet packet transform as the preprocessing, and the wavelet packet transformed signal uses least mean square algorithm to implement the ~adaptive beamforming. White noise can be wiped off under wavelet packet transform according to the different characteristics of signal and white under the wavelet packet transform. Theoretical analysis and simulations demonstrate that the proposed WP-ABF algorithm converges faster than the conventional adaptive beamforming algorithm and the wavelet transform-based beamforming algorithm. Simulation results also reveal that the convergence of the algorithm relates closely to the wavelet base and series; that is, the algorithm convergence gets better with the increasing of series, and for the same series of wavelet base the convergence gets better with the increasing of regularity.
文摘This work describes a novel adaptive matrix/vector gradient (AMVG) algorithm for design of IIR filters and ARMA signal models. The AMVG algorithm can track to IIR filters and ARMA systems having poles also outside the unit circle. The time reversed filtering procedure was used to treat the unstable conditions. The SVD-based null space solution was used for the initialization of the AMVG algorithm. We demonstrate the feasibility of the method by designing a digital phase shifter, which adapts to complex frequency carriers in the presence of noise. We implement the half-sample delay filter and describe the envelope detector based on the Hilbert transform filter.
文摘Noise cancellation is very important in the field of signal processing. Inthis paper, the designation of a modified LMS Adaptive Noise Cancellation is demonstrated in detail;the model is simulated. We have compared the performance of the new model with the old model. Theresult of the experiments shows that this designation improves the noise cancellation's performancegreatly.
基金The authors are grateful for the support received from the National Key R&D Project from the Minister of Science and Technology(Nos.2021YFA1201601 and 2021YFA1201604)the Open Research Project Programme of the State Key Laboratory of Internet of Things for Smart City(University of Macao)(No.SKL-IoTSC(UM)-2021-2023/ORPF/A17/2022).
文摘The development of automation industry is inseparable from the progress of sensing technology.As a promising self-powered sensing technology,the durability and stability of triboelectric sensor(TES)have always been inevitable challenges.Herein,a continuous charge supplement(CCS)strategy and an adaptive signal processing(ASP)method are proposed to improve the lifetime and robustness of TES.The CCS uses low friction brushes to increase the surface charge density of the dielectric,ensuring the reliability of sensing.A triboelectric mechanical motion sensor(TMMS)with CCS is designed,and its electrical signal is hardly attenuated after 1.5 million cycles after reasonable parameter optimization,which is unprecedented in linear TESs.After that,the dynamic characteristics of the CCS-TMMS are analyzed with error rates of less than 1%and 2%for displacement and velocity,respectively,and a signal-to-noise ratio of more than 35 dB.Also,the ASP used a signal conditioning circuit for impedance matching and analog-to-digital conversion to achieve a stable output of digital signals,while the integrated design and manufacture of each hardware module is achieved.Finally,an intelligent logistics transmission system(ILTS)capable of wirelessly monitoring multiple motion parameters is developed.This work is expected to contribute to automation industries such as smart factories and unmanned warehousing.
