An improved SCOT double weighted quadratic correlation time delay estimation algorithm based on infrasound signal

Abstract

In the pipeline leak location technology by detecting Infrasound signals, time delay estimation algorithm has become a significant method, but the quality of time delay estimation calculation method determines the accuracy of location. This article proposes an improved Smooth Coherent Transform (SCOT) generalized weight function based on the quadratic correlation delay estimation algorithm, defined as SCOT-γ to suppress the false peak of the signal by adding weight to the SCOT weight function , the two cross-correlations in the quadratic cross-correlation algorithm are weighted separately with the improved weight function. In this paper, MATLAB is used for experimental simulation. First, Infrasound signals with Gaussian white noise are constructed,then the influence of the weighting factor on the delay estimation performance is verified through multiple experiments, and the optimal value of the weighting factor γ is determined at the same time. Then perform cross correlation peak detection on the SCOT primary weighting method, SCOT-γ once weighting method, and SCOT-γ double weighting method and compare the noise reduction effect; finally, compare the performance of the three algorithms by calculating the root mean square error of the delay value of the three algorithms. The results show that the improved SCOT double weighted quadratic correlation time delay estimation algorithm has better anti-noise performance and higher precision.