群时延傅里叶分解模型及其估计方法

建立了基于三角函数级数的群时延模型,并理论证明了仅采用有限阶数的三角函数群时延即可表征任意群时延对信号相关峰的影响。在此基础上,通过测量信号相关峰,并与不同三角函数群时延组合下的相关峰进行匹配搜索即可估计群时延的三角函数分解级数,从而估计得到相关峰影响等效的群时延特性。仿真中,采用该方法估计得到的群时延特性对滤波器进行修正后,信号相关峰与经过滤波器之前的信号相关峰高度吻合,时延估计偏差在0.1 ns之内。

Fourier decomposition model of group delay and its estimation method

A group delay model based on trigonometric function series was proposed. And it was theoretically proved that only a finite order of trigonometric function group delay can characterize the influence of arbitrary group delay on signal correlation peaks. On this basis, the trigonometric decomposition series of the group delay were obtained by measuring the correlation peaks and matching the correlation peaks under different combinations of trigonometric function group delays. As a result, the equivalent group delay with similar effects on the correlation peaks was obtained. Simulation results show that the correlation peak of the signal is approximately the same as that of the ideal correlation peak, and the delay estimation error is less than 0.1 ns at different delay time intervals after calibration of the channel by using the group delay estimated by this method.