脉冲噪声环境下的自适应时间延迟估计新方法

基于自适应分数低阶协方差(AFLC)的时间延迟估计方法在脉冲噪声环境下具有良好的韧性,但是算法中参数a和b的取值对于算法的估计精度有一定的影响。针对信号噪声的非平稳特性,该文提出一种动态参数估计方法,并在此基础上提出一种不受约束条件限制的修正的自适应分数低阶协方差(M-AFLC)算法。计算机仿真结果表明,递推参数估计方法在平稳和非平稳噪声环境下都能够很好地工作,M-AFLC算法既保留了AFLC算法的全部优点,又避免了AFLC算法在约束条件不满足时的性能退化。

A New Method of Adaptive Time Delay Estimation in Impulsive Noise Environments

The Adaptive Fractional Lower order Covariance (AFLC) time delay estimation method performs robust under impulsive noise environments, but the values of parameters a and b have effects on estimated precision. According to the non-stationary property of noises, this paper proposes a dynamic parameter estimation method and further proposes a Modified Adaptive Fractional Lower order Covariance (M-AFLC) method. Computer simulation indicates that the iterative parameter estimation method performs well under both stationary and non-stationary noise conditions. It also shows that the M-AFLC maintains the merits of the AFLC, and at the same time the proposed method avoids the degradation of AFLC while the restriction unsatisfied.