基于最小CIM准则的Farrow结构分数时延估计

Fractional time delay estimation method based on the minimum CIM and the Farrow structure

提出了一种基于最小相关熵诱导距离(CIM)和Farrow结构的分数时延估计算法。该算法具有较强的抗脉冲噪声的能力,且所需观测数据较少,时延估计结果精度较高。理论分析和仿真实验表明,所提算法的估计精度和抗脉冲噪声性能均优于基于分数低阶统计量的LETDE算法。

A fractional time delay estimation algorithm is proposed which is based on the minimum CIM and the Farrow structure（referred to as MCIMFarrow）. The proposed MCIMFarrow algorithm performs well in symmetric Alpha stable noise conditions. And it needs little observation data to gain high accuracy estimation results. The theoretical analyses and the simulation results show that the MCIMFarrow is much better than the LETDE algorithm based on the fractional lower order moments in the accuracy of the time delay estimation and the robustness in impulsive noise conditions.