To reduce the spectral distortion,a Hidden Markov Model-based narrowband speech bandwidth extension algorithm is presented.Firstly,the parameters which have higher mutual information with wideband envelope were extrac...To reduce the spectral distortion,a Hidden Markov Model-based narrowband speech bandwidth extension algorithm is presented.Firstly,the parameters which have higher mutual information with wideband envelope were extracted to constitute the feature vector,and then a posterior probability was calculated via the joint probability of the partial observation feature vector sequence and the markov states.Secondly,based on the posterior probability,the wideband envelope was estimated using Bayesian parameter estimation method and minimum mean square error criteria.For estimation of wideband excitation signal,intermediate frequency extension algorithm is proposed based on the harmonic correlation between the low frequency and high frequency.The experimental results show that,compared with the traditional bandwidth extension algorithm based on Hidden Markov Model,the average spectral distortion is reduced by 0.187 dB and the number of speech frame with spectral distortion over10dB is decreased by 34.3%.展开更多
In a GPS illuminator based passive radar system,estimation of direction of arriving(DOA) of multiple targets is a difficult problem due to strong interference.A two-stage method combining extensive cancellation algori...In a GPS illuminator based passive radar system,estimation of direction of arriving(DOA) of multiple targets is a difficult problem due to strong interference.A two-stage method combining extensive cancellation algorithm(ECA) and sparse representation is proposed.In the first stage,ECA algorithm is used to eliminate the direct-path and multi-path interference.In the second stage,sparse representation of improved weight constraints based on L1 norm is adopted to estimate DOA and suppress the interference.Simulation results show that the proposed method can effectively estimate DOA in low computation complexity without estimating the disturbance parameter.展开更多
In passive bistatic radar,the computational efficiency of clutter suppression algorithms remains low,due to continuous increases in bandwidth for potential illuminators of opportunity and the use of multi-source detec...In passive bistatic radar,the computational efficiency of clutter suppression algorithms remains low,due to continuous increases in bandwidth for potential illuminators of opportunity and the use of multi-source detection frameworks.Accordingly,we propose a lightweight version of the extensive cancellation algorithm(ECA),which achieves clutter suppression performance comparable to that of ECA while reducing the computational and space complexities by at least one order of magnitude.This is achieved through innovative adjustments to the reference signal subspace matrix within the ECA framework,resulting in a redefined approach to the computation of the autocorrelation matrix and cross-correlation vector.This novel modification significantly simplifies the computational aspects.Furthermore,we introduce a dimension-expanding technique that streamlines clutter estimation.Overall,the proposed method replaces the computation-intensive aspects of the original ECA with fast Fourier transform(FFT)and inverse FFT operations,and eliminates the construction of the memory-intensive signal subspace.Comparing the proposed method with ECA and its batched version(ECA-B),the central advantages are more streamlined implementation and minimal storage requirements,all without compromising performance.The efficacy of this approach is demonstrated through both simulations and field experimental results.展开更多
文摘To reduce the spectral distortion,a Hidden Markov Model-based narrowband speech bandwidth extension algorithm is presented.Firstly,the parameters which have higher mutual information with wideband envelope were extracted to constitute the feature vector,and then a posterior probability was calculated via the joint probability of the partial observation feature vector sequence and the markov states.Secondly,based on the posterior probability,the wideband envelope was estimated using Bayesian parameter estimation method and minimum mean square error criteria.For estimation of wideband excitation signal,intermediate frequency extension algorithm is proposed based on the harmonic correlation between the low frequency and high frequency.The experimental results show that,compared with the traditional bandwidth extension algorithm based on Hidden Markov Model,the average spectral distortion is reduced by 0.187 dB and the number of speech frame with spectral distortion over10dB is decreased by 34.3%.
基金Supported by the National Natural Science Foundation of China(No.31270737)Specialized Research Fund for the Doctoral Program of Higher Education(No.20110062110002)the Fundamental Research Funds for the Central Universities(No.2572014EB03,DL13BB16)
文摘In a GPS illuminator based passive radar system,estimation of direction of arriving(DOA) of multiple targets is a difficult problem due to strong interference.A two-stage method combining extensive cancellation algorithm(ECA) and sparse representation is proposed.In the first stage,ECA algorithm is used to eliminate the direct-path and multi-path interference.In the second stage,sparse representation of improved weight constraints based on L1 norm is adopted to estimate DOA and suppress the interference.Simulation results show that the proposed method can effectively estimate DOA in low computation complexity without estimating the disturbance parameter.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(No.LZ23F030002)the Science and Technology Program of Zhejiang Provincial Department of Transportation(No.2024012)the Talent Funding Project of Zhejiang Institute of Communications(Nos.822321KY0127 and 2024JK05)。
文摘In passive bistatic radar,the computational efficiency of clutter suppression algorithms remains low,due to continuous increases in bandwidth for potential illuminators of opportunity and the use of multi-source detection frameworks.Accordingly,we propose a lightweight version of the extensive cancellation algorithm(ECA),which achieves clutter suppression performance comparable to that of ECA while reducing the computational and space complexities by at least one order of magnitude.This is achieved through innovative adjustments to the reference signal subspace matrix within the ECA framework,resulting in a redefined approach to the computation of the autocorrelation matrix and cross-correlation vector.This novel modification significantly simplifies the computational aspects.Furthermore,we introduce a dimension-expanding technique that streamlines clutter estimation.Overall,the proposed method replaces the computation-intensive aspects of the original ECA with fast Fourier transform(FFT)and inverse FFT operations,and eliminates the construction of the memory-intensive signal subspace.Comparing the proposed method with ECA and its batched version(ECA-B),the central advantages are more streamlined implementation and minimal storage requirements,all without compromising performance.The efficacy of this approach is demonstrated through both simulations and field experimental results.
