一种自适应时延估计的新方法

A Kind of New Method about Adaptive Time Delay Estimation

最小均方(LMS)算法可用来进行时延估计。当算法收敛后,可以根据滤波器权系数最大值的位置估计整数倍采样周期的时延。为了估计非整数倍采样周期的时延,常用SINC函数插值法和约束自适应方法。利用SINC函数的特点和拉格朗日条件极值,对自适应时延估计的滤波器权系数做了改进,提出了新的约束自适应时延估计方法。仿真实验表明,提出方法的性能优于传统的自适应时延估计算法。

The least mean square（LMS） algorithm can be used to perform the time delay estimation （TDE）. After the algorithm was convergented,the time delay of integer times sampling period can be estimated according to the position of the max weight coefficient max of the filter. The SINC function interpolation method and constrained adaptive method are usually used to estimate the time delay of no-integer times sampling period. This paper improves the weight coefficient of the filter for the adaptive time delay estimation by means of the characteristic of SINC function and Lagrange condition extremum,presents the new constrained adaptive time delay estimation method. The simulation experiment shows that the performance of the proposed method exceeds that of the traditional adaptive TDE method.