A Time Delay Estimation Algorithm Based on the Weighted Correntropy Spectral Density.

Accuracy and resistance to noise are two important aspects of time delay estimation algorithms. The cross power-spectrum phase algorithm is a classic time delay estimation algorithm. It is accurate but not robust to noise. Its performance deteriorates or even fails under impulsive noise. The improved cross power-spectrum phase algorithms based on fractional lower-order statistics rely on a priori knowledge of impulsive noise. In this paper, we propose a novel time delay estimation algorithm based on the weighted correntropy spectral density. The proposed method works well under impulsive noise because it is based on correntropy theory and its resistance to noise is further strengthened by the weighting process in the frequency domain. Our theoretical analysis and simulations demonstrate that the proposed method is very accurate in the presence of Gaussian or impulsive noise with a low generalized signal-to-noise ratio.