Time delay estimation based on variational mode decomposition

Jing-Yi Lu,Dong Ye,Wen-Ping Ma

doi:10.1177/1687814016688587

Abstract

In order to improve the time delay estimation of colored noise signals, this article proposes generalized cross-correlation time delay estimation based on variational mode decomposition. First of all, we put forward the signal energy detection criterion to extract the effective signal from the signal, which can reduce the amount of calculation and improve the real-time performance. Second, the effective signal is decomposed into a number of intrinsic mode functions using variational mode decomposition. The correlation coefficients of each intrinsic mode function and the original signal are calculated. The article reconstructed signal with intrinsic mode functions which extract useful intrinsic mode functions by defaulting the correlation coefficient threshold. Finally, this article uses generalized cross-correlation to estimate time delay of the reconstructed signal. Theoretical analysis and simulation results show that the accurate time delay estimation can be obtained under the condition of color noise by the proposed method. The measurement accuracy of the proposed method is 15 times that of the generalized cross-correlation, and the running time of the proposed method is 4.0601 times faster than that of the generalized cross-correlation algorithm. The proposed method can reduce the computation and the running time of the system and also improve the measurement accuracy.

Highlights

Typical estimation methods are adaptive Time delay estimation (TDE), weighted generalized phase TDE, least mean square (LMS) TDE, and generalized cross-correlation (GCC) TDE based on empirical mode decomposition (EMD), which are improved on the basis of cross-correlation TDE
By comparing the results of GCC TDE and the presented method, it is concluded that the delay error of the former is 15 times that of the latter, and the running time of the program is 4.0601 times that of the latter
A novel TDE method is presented to overcome the drawbacks of the GCC TDE

Summary

Introduction

Time delay estimation (TDE) is one of the key problems in passive acoustic localization based on microphone array, and it has very important theoretical significance and practical application value.[1,2,3,4] Typical estimation methods are adaptive TDE, weighted generalized phase TDE, least mean square (LMS) TDE, and generalized cross-correlation (GCC) TDE based on empirical mode decomposition (EMD), which are improved on the basis of cross-correlation TDE. The algorithm first uses the inverse square law and the size of the microphone array sound signal transmission to extract the effective signal, thereby reducing the amount of calculation and improving the real time It decomposes the effective signal into a plurality of the intrinsic mode functions (IMF) by VMD and calculates the correlation coefficient of the IMF and the original signal, determines the IMF number of reconstructed signal using the default correlation coefficient threshold. According to the inverse square law of propagation of sound signal, the variation in signal energy is used to determine the starting point and the effective length of the signal in the process of calculating the actual signal time delay, which achieves the purpose of reducing the amount of computation.

Experiments and analysis Simulation experiment

Conclusion