SEPARATION OF MULTIPLE TIME DELAYS USING NEW SPECTRAL ESTIMATION SCHEMES

The problem of estimating multiple time delays in presence of colored noise is considered in this paper. This problem is first converted to a high-resolution frequency estimation problem. Then, the sample lagge d covariance matrices of the resulting signal are computed and studied in terms of their eigenstructure. These matrices are shown to be as e ffective in extracting bases for the signal and noise subspaces as the standard autocorrelation matrix, which is normally used in MUSIC and the pencil-based methods. Frequency estimators are then derived using these subspaces, The effectiveness of the method is demonstrated on tw o examples: a standard frequency estimation problem in presence of col ored noise and a real-world problem that involves separation of multip le specular components from the acoustic backscattered from an underwa ter target.