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中文摘要：
依据零阶统计量理论，给出对数矩过程、对数宽平稳及对数各态遍历的定义，提出一种韧性的归一化自适应时间延迟估计方法（简称NZOSTDE）。该算法用FIR滤波器对两个含有脉冲噪声的观测信号建模，利用不存在有限方差的脉冲信号经过对数变换后其各阶矩的存在性和几何功率的概念，在对数域基于最小均方误差（LMS）准则归～化自适应得到FIR滤波器的系数，该系数最大值对应的序号就是时间延迟的估计值。本文提出的新算法克服了基于分数低阶统计量（FLOS）算法的局限性。计算机仿真实验表明，NZOSTDE算法在强脉冲噪声环境下比归一化最小平均P范数时间延迟估计方法（简称NLMPTDE）算法更具有韧性。
英文摘要：
Based on zero-order statistics,the logarithmic moment processes,logarithmic wide sense stationary and ergodic random processes are defined. A robust normalized adaptive approach for time delay estimation （TDE） , referred to as NZOSTDE,is proposed in the presence of an impulsive noise. Through a logarithmic transform, the impulsive signals without finite variance become the logarithmicorder signals. In this case, all of the moments are finite. The NZOSTDE algorithm considers this property and the concept of geometric power, then the FIR filter models the two received signals added impulsive noises and its coefficients can be adaptive obtained under least mean square （LMS） error criterion in the logarithmic domain. Accordingly, the estimation of time delay between the two sources is the time index of the maximum in the coefficients. The proposed novel approach overcomes the shortcoming of algorithms based on fractional lower-order statistics （FLOS）. Computer simulation results show that NZOSTDE algorithm is more robust than normalized least mean p norm time delay estimation, referred to as NLMPTDE,under very impulsive environments.
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