基于分段CEEMD降噪的时延估计研究

为了提高信号非平稳、采样点数较多条件下的时延估计精度和速度,提出了一种基于分段CEEMD降噪的广义互相关时延估计方法。该方法首先将原始信号划分为等长的小信号段,再利用CEEMD阈值降噪方法滤除各小段信号的噪声成分,连接降噪小信号段构成原始信号的降噪信号,最后根据降噪信号的互相关峰值来估计时延。针对该方法中的分段段数和添噪次数的选取问题,在研究这两个参数对仿真人走动信号降噪精度和计算耗时等性能的影响的基础上,给出了参数的具体选择范围。将该方法应用于声定位系统的时延估计中,结果表明:在信号采样点数较多、低信噪比的情况下该方法仍能够较为快速、准确地估计时延。

Research on time delay estimation based on signal chopping-based CEEMD de-noising method

In order to improve the accuracy and speed of TDE in the case that the signals are non-stationary and con-tain a large number of sampling points , a new method for generalized cross =correlation TDE method on the basis of signal chopping-based CEEMD de-noising is proposed in this paper .Firstly, the original large-signal is divided into several smaller sections with equal length for each one , and then, each section is de-noised by using CEEMD thresh-old de-noising method , all the smaller sections are combined to obtain the de-noised version of the original signals . Furthermore , the time delay value is estimated according to the cross-correlation peak of the de-noised signals .For the selection of the numbers of sections and added noise in the process of TDE , the specific range of these two parameters is given by exploring the effect of these two parameters on de-noising precision , calculation time and other performance of the dummy walking signal .Finally, this method is applied to the TDE in acoustic source localization system .The results show that this method can still estimate time delay value rapidly and accurately when the signals contain a large number of sampling points and the SNR is low .