Time delay estimation based on variational mode decomposition

Abstract

In order to improve the time delay estimation of colored noise signals, this article proposes generalized crosscorrelation 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.

Development of Time Delay Estimation Algorithm Using Fuzzy Based Optimized Iterative Unscented Kalman Filter

“…This work utilizes reenactments and eeting recurrence portrayals to look at the issues related with TDE of coordinated separating based objective distinguishing proof. Time-delay estimation is an important research aspect in the signal processing domain, and is used to determine the time offset of some signal compared with the referenced signal [3]. For example, one of the important applications of wireless sensor networks is localization, and to locate an object accurately in the wireless sensor networks, the measurement based on time-delay is the most ideal method.…”