Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm

The time delay estimation algorithm is one of the important factors of sound source localization. The generalized weighted adaptive time delay estimation algorithm is limited by the environmental conditions of signal and noise, and has great limitations in non-Gaussian environments. In order to make the algorithm suitable for non-Gaussian environments, and to retain the advantages of the algorithm in effectively suppressing harmonics, this paper combines the minimum average P norm (LMP) with the generalized weighting function, and proposes a method based on the minimum average P norm. The generalized weighted adaptive time delay estimation algorithm of the number can make the algorithm suitable for non-Gaussian environments, and for the shortcomings of slow iteration speed and large calculation amount for the minimum average P norm, the Sigmoid function is introduced to further improve the parameter selection in the algorithm. MATLAB simulation experiments show that the algorithm in this paper can effectively suppress the existence of harmonics in a non-Gaussian environment, and has strong convergence, high accuracy of time delay estimation, and fast iteration speed. It can be based on time delay estimation in a non-Gaussian environment. The positioning plays a certain role.