This paper is mainly to deal with the problem of direction of arrival(DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive ...This paper is mainly to deal with the problem of direction of arrival(DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive noise as α-stable distribution, new methods which combine the sparse signal representation technique and fractional lower order statistics theory are proposed. In the new algorithms, the fractional lower order statistics vectors of the array output signal are sparsely represented on an overcomplete basis and the DOAs can be effectively estimated by searching the sparsest coefficients. To enhance the robustness performance of the proposed algorithms,the improved algorithms are advanced by eliminating the fractional lower order statistics of the noise from the fractional lower order statistics vector of the array output through a linear transformation. Simulation results have shown the effectiveness of the proposed methods for a wide range of highly impulsive environments.展开更多
Evoked potentials (EPs) have been widely used to quantify neurological system properties. Tra-ditional EP analysis methods are developed under the condition that the background noises in EP are Gaussian distributed. A...Evoked potentials (EPs) have been widely used to quantify neurological system properties. Tra-ditional EP analysis methods are developed under the condition that the background noises in EP are Gaussian distributed. Alpha stable distribution, a generalization of Gaussian, is better for modeling impulsive noises than Gaussian distribution in biomedical signal proc-essing. Conventional blind separation and es-timation method of evoked potentials is based on second order statistics or high order Statis-tics. Conventional blind separation and estima-tion method of evoked potentials is based on second order statistics (SOS). In this paper, we propose a new algorithm based on minimum dispersion criterion and fractional lower order statistics. The simulation experiments show that the proposed new algorithm is more robust than the conventional algorithm.展开更多
针对α稳定分布噪声环境下的自适应滤波问题,提出一种新的基于梯度范数的变步长归一化最小平均p范数(variable step-size normalized least mean p-norm,VSS-NLMP)算法。该算法首先对梯度矢量进行加权平滑,以减小梯度噪声的影响,然后利...针对α稳定分布噪声环境下的自适应滤波问题,提出一种新的基于梯度范数的变步长归一化最小平均p范数(variable step-size normalized least mean p-norm,VSS-NLMP)算法。该算法首先对梯度矢量进行加权平滑,以减小梯度噪声的影响,然后利用梯度矢量能够跟踪自适应过程的均方偏差这一特点,利用梯度矢量的欧氏范数控制步长的变化。给出了新算法的迭代过程,然后对其收敛性进行分析,仿真结果表明本算法较现有变步长NLMP算法有更好的性能。展开更多
针对基于相关函数的波达方向(direction of arrival,DOA)估计方法在冲击噪声环境下性能下降明显甚至失效的问题,提出基于相关熵(Correntropy)的二维ESPRIT算法;该方法利用相关熵在冲击噪声环境下具有鲁棒性的优点,将受干扰信号的自相关...针对基于相关函数的波达方向(direction of arrival,DOA)估计方法在冲击噪声环境下性能下降明显甚至失效的问题,提出基于相关熵(Correntropy)的二维ESPRIT算法;该方法利用相关熵在冲击噪声环境下具有鲁棒性的优点,将受干扰信号的自相关函数替换为相关熵函数,并结合二维ESPRIT算法实现在冲击噪声环境下进行二维DOA估计;仿真表明,与基于分数低阶统计(Fractional Lower Order Statistics,FLOS)算法相比,该算法呈现明显优势,特别在高的冲击噪声条件下(1<α<1.5)能对信源方向进行更加有效的估计,且均方误差值仍保持很低。展开更多
基金supported in part by the National Natural Science Foundation of China(61301228,61371091)the Fundamental Research Funds for the Central Universities(3132014212)
文摘This paper is mainly to deal with the problem of direction of arrival(DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive noise as α-stable distribution, new methods which combine the sparse signal representation technique and fractional lower order statistics theory are proposed. In the new algorithms, the fractional lower order statistics vectors of the array output signal are sparsely represented on an overcomplete basis and the DOAs can be effectively estimated by searching the sparsest coefficients. To enhance the robustness performance of the proposed algorithms,the improved algorithms are advanced by eliminating the fractional lower order statistics of the noise from the fractional lower order statistics vector of the array output through a linear transformation. Simulation results have shown the effectiveness of the proposed methods for a wide range of highly impulsive environments.
文摘Evoked potentials (EPs) have been widely used to quantify neurological system properties. Tra-ditional EP analysis methods are developed under the condition that the background noises in EP are Gaussian distributed. Alpha stable distribution, a generalization of Gaussian, is better for modeling impulsive noises than Gaussian distribution in biomedical signal proc-essing. Conventional blind separation and es-timation method of evoked potentials is based on second order statistics or high order Statis-tics. Conventional blind separation and estima-tion method of evoked potentials is based on second order statistics (SOS). In this paper, we propose a new algorithm based on minimum dispersion criterion and fractional lower order statistics. The simulation experiments show that the proposed new algorithm is more robust than the conventional algorithm.
文摘针对α稳定分布噪声环境下的自适应滤波问题,提出一种新的基于梯度范数的变步长归一化最小平均p范数(variable step-size normalized least mean p-norm,VSS-NLMP)算法。该算法首先对梯度矢量进行加权平滑,以减小梯度噪声的影响,然后利用梯度矢量能够跟踪自适应过程的均方偏差这一特点,利用梯度矢量的欧氏范数控制步长的变化。给出了新算法的迭代过程,然后对其收敛性进行分析,仿真结果表明本算法较现有变步长NLMP算法有更好的性能。
文摘针对基于相关函数的波达方向(direction of arrival,DOA)估计方法在冲击噪声环境下性能下降明显甚至失效的问题,提出基于相关熵(Correntropy)的二维ESPRIT算法;该方法利用相关熵在冲击噪声环境下具有鲁棒性的优点,将受干扰信号的自相关函数替换为相关熵函数,并结合二维ESPRIT算法实现在冲击噪声环境下进行二维DOA估计;仿真表明,与基于分数低阶统计(Fractional Lower Order Statistics,FLOS)算法相比,该算法呈现明显优势,特别在高的冲击噪声条件下(1<α<1.5)能对信源方向进行更加有效的估计,且均方误差值仍保持很低。
