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 lagged covariance matrices of the resulting signal are computed and studied in terms of their eigenstructure. These matrices are shown to be as effective 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 two examples: a standard frequency estimation problem in presence of colored noise and a real-world problem that involves separation of multiple specular components from the acoustic backscattered from an underwater target.
Bibliographical noteFunding Information:
Manuscript received August 6, 1996; revised December 5, 1997. This work was supported by the Office of Naval Research (ONR 321TS). The Technical Agent was Coastal Systems Station, Panama City, FL. The associate editor coordinating the review of this paper and approving it for publication was Dr. Eric Moulines.
- Data decimation
- Spectral estimation
- Underwater acoustics