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
In order to solve the problem of coherent signal subspace method(CSSM) depending on the estimated accuracy of signal subspace, a new direction of arrival(DOA) estimation method of wideband source, which is based on it...In order to solve the problem of coherent signal subspace method(CSSM) depending on the estimated accuracy of signal subspace, a new direction of arrival(DOA) estimation method of wideband source, which is based on iterative adaptive spectral reconstruction, is proposed. Firstly, the wideband signals are divided into several narrowband signals of different frequency bins by discrete Fourier transformation(DFT). Then, the signal matched power spectrum in referenced frequency bins is computed, which can form the initial covariance matrix. Finally, the linear restrained minimum variance spectral(Capon spectral) of signals in other frequency bins are reconstructed using sequential iterative means, so the DOA can be estimated by the locations of spectral peaks. Theoretical analysis and simulation results show the proposed method based on the iterative spectral reconstruction for the covariance matrices of all sub-bands can avoid the problem of determining the signal subspace accurately with the coherent signal subspace method under the conditions of small samples and low signal to noise ratio(SNR), and it can also realize full dimensional focusing of different sub-band data, which can be applied to coherent sources and can significantly improve the accuracy of DOA estimation.展开更多
This paper studies the adaptive beamforming algorithm based on the frequency diverse array(FDA)array where the interference is located at the same angle(but different range)with the target.We take the cross subarray-b...This paper studies the adaptive beamforming algorithm based on the frequency diverse array(FDA)array where the interference is located at the same angle(but different range)with the target.We take the cross subarray-based FDA with sinusoidal frequency offset(CSB sin-FDA)as the receiving array instead of the basic FDA.The sampling covariance matrix under insufficient snapshot can be corrected by the automatic diagonal loading method.On the basis of decomposing the mismatched steering vector error into a vertical component and a parallel one,this paper searches the vertical component of the error by the quadratic constraint method.The numerical simulation verifies that the beamformer based on the CSB sin-FDA can effectively hold the mainlobe at the target position when the snapshot is insufficient or the steering vector is mismatched.展开更多
A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original...A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly.An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam,respectively.The optimal weight vector can be obtained after convergence.The required computational complexity is evaluated for the proposed technique,which is on the order of O(N)and less than that of the conventional LCMV method.The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced.This scheme is easy to be implemented on a distributed computer/digital signal processor(DSP)system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array.Then,the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations.Compared with some recent adaptive monopulse estimation methods,a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.展开更多
This paper presents a hardware architecture using mixed pipeline and parallel processing for complex division based on dichotomous coordinate descent(DCD) iterations. The objective of the proposed work is to achieve l...This paper presents a hardware architecture using mixed pipeline and parallel processing for complex division based on dichotomous coordinate descent(DCD) iterations. The objective of the proposed work is to achieve low-latency and resource optimized complex divider architecture in adaptive weight computation stage of minimum variance distortionless response(MVDR)algorithm. In this work, computation of complex division is modeled as a 2×2 linear equation solution problem and the DCD algorithm allows linear systems of equations to be solved with high degree of computational efficiency. The operations in the existing DCD algorithm are suitably parallel pipelined and the performance is optimized to 2 clock cycles per iteration. To improve the degree of parallelism, a parallel column vector read architecture is devised.The proposed work is implemented on the field programmable gate array(FPGA) platform and the results are compared with state-of-art literature. It concludes that the proposed architecture is suitable for complex division in adaptive weight computation stage of MVDR beamformer. We demonstrate the performance of the proposed architecture for MVDR beamformer employed in medical ultrasound imaging applications.展开更多
A novel dual control method is proposed for the stochastic systems with unknown parameters, which converts the unsolvable dynamic programming problem into a tractable twostep ahead minimum variance control problem in ...A novel dual control method is proposed for the stochastic systems with unknown parameters, which converts the unsolvable dynamic programming problem into a tractable twostep ahead minimum variance control problem in a stochastic suboptimal view. Innovation variance is used to improve the learning effect, and the instant weight is introduced to reduce the influence of the future output estimation error on the system. Simulation results show the satisfactory performance of the new controller.展开更多
The control problem for single-input single-output（SISO） systems in the presence of mixed uncertainties, both stochastic and deterministic uncertainties, is considered. The stochastic uncertainties are modeled as ex...The control problem for single-input single-output（SISO） systems in the presence of mixed uncertainties, both stochastic and deterministic uncertainties, is considered. The stochastic uncertainties are modeled as exogenous noises, while the deterministic uncertainties are time invariant and appear as the unknown parameters which lie in a bounded interval. Based on a subdivision for the continuous interval, a robust adaptive controller is designed. The controller can not only realize the system output to track the desired output, but also learn a more accurate interval which contains the true value of the unknown parameter with a learning error given in advance. An example is given finally to demonstrate the effectiveness of the proposed method.展开更多
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(61671352)the open foundation of Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education(Guilin University of Electronic Technology)(CRKL160206)Xi’an University of Science and Technology Doctor(after)Start Gold Project(2017QDJ018)
文摘In order to solve the problem of coherent signal subspace method(CSSM) depending on the estimated accuracy of signal subspace, a new direction of arrival(DOA) estimation method of wideband source, which is based on iterative adaptive spectral reconstruction, is proposed. Firstly, the wideband signals are divided into several narrowband signals of different frequency bins by discrete Fourier transformation(DFT). Then, the signal matched power spectrum in referenced frequency bins is computed, which can form the initial covariance matrix. Finally, the linear restrained minimum variance spectral(Capon spectral) of signals in other frequency bins are reconstructed using sequential iterative means, so the DOA can be estimated by the locations of spectral peaks. Theoretical analysis and simulation results show the proposed method based on the iterative spectral reconstruction for the covariance matrices of all sub-bands can avoid the problem of determining the signal subspace accurately with the coherent signal subspace method under the conditions of small samples and low signal to noise ratio(SNR), and it can also realize full dimensional focusing of different sub-band data, which can be applied to coherent sources and can significantly improve the accuracy of DOA estimation.
基金supported by the National Natural Science Foundation of China(61503408)
文摘This paper studies the adaptive beamforming algorithm based on the frequency diverse array(FDA)array where the interference is located at the same angle(but different range)with the target.We take the cross subarray-based FDA with sinusoidal frequency offset(CSB sin-FDA)as the receiving array instead of the basic FDA.The sampling covariance matrix under insufficient snapshot can be corrected by the automatic diagonal loading method.On the basis of decomposing the mismatched steering vector error into a vertical component and a parallel one,this paper searches the vertical component of the error by the quadratic constraint method.The numerical simulation verifies that the beamformer based on the CSB sin-FDA can effectively hold the mainlobe at the target position when the snapshot is insufficient or the steering vector is mismatched.
基金supported by the National Natural Science Foundation of China(11273017)
文摘A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly.An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam,respectively.The optimal weight vector can be obtained after convergence.The required computational complexity is evaluated for the proposed technique,which is on the order of O(N)and less than that of the conventional LCMV method.The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced.This scheme is easy to be implemented on a distributed computer/digital signal processor(DSP)system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array.Then,the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations.Compared with some recent adaptive monopulse estimation methods,a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.
基金supported by Microelectronics Division of the Ministry of Electronics and Information Technology,Government of India,under SMDP-C2SD Project(9(1)/2014–MDD)
文摘This paper presents a hardware architecture using mixed pipeline and parallel processing for complex division based on dichotomous coordinate descent(DCD) iterations. The objective of the proposed work is to achieve low-latency and resource optimized complex divider architecture in adaptive weight computation stage of minimum variance distortionless response(MVDR)algorithm. In this work, computation of complex division is modeled as a 2×2 linear equation solution problem and the DCD algorithm allows linear systems of equations to be solved with high degree of computational efficiency. The operations in the existing DCD algorithm are suitably parallel pipelined and the performance is optimized to 2 clock cycles per iteration. To improve the degree of parallelism, a parallel column vector read architecture is devised.The proposed work is implemented on the field programmable gate array(FPGA) platform and the results are compared with state-of-art literature. It concludes that the proposed architecture is suitable for complex division in adaptive weight computation stage of MVDR beamformer. We demonstrate the performance of the proposed architecture for MVDR beamformer employed in medical ultrasound imaging applications.
文摘A novel dual control method is proposed for the stochastic systems with unknown parameters, which converts the unsolvable dynamic programming problem into a tractable twostep ahead minimum variance control problem in a stochastic suboptimal view. Innovation variance is used to improve the learning effect, and the instant weight is introduced to reduce the influence of the future output estimation error on the system. Simulation results show the satisfactory performance of the new controller.
基金supported by the National Natural Science Foundation of China(61273127U1534208)+2 种基金the Key Program of National Natural Science Foundation of China(61533014)the Key Laboratory for Fault Diagnosis and Maintenance of Spacecraft in Orbit(SDML-OF2015004)the Science and Technology Preject of Shaanxi Province(2016GY-108)
文摘The control problem for single-input single-output（SISO） systems in the presence of mixed uncertainties, both stochastic and deterministic uncertainties, is considered. The stochastic uncertainties are modeled as exogenous noises, while the deterministic uncertainties are time invariant and appear as the unknown parameters which lie in a bounded interval. Based on a subdivision for the continuous interval, a robust adaptive controller is designed. The controller can not only realize the system output to track the desired output, but also learn a more accurate interval which contains the true value of the unknown parameter with a learning error given in advance. An example is given finally to demonstrate the effectiveness of the proposed method.
