Separation of multiple time delays using new spectral estimation schemes Hasan, Mohammed A. ; Azimi-Sadjadi, Mahmood R. ; Dobeck, Gerald J. "This work was supported by the Office of Naval Research (ONR 321TS). The Technical Agent was Coastal Systems Station, Panama City, FL." 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. Colorado State University. Libraries 1998 text ; image application/pdf ECEmra00044.pdf FACFECEN100524ARTI eng c1998 IEEE
Separation of multiple time delays using new spectral estimation schemes
Hasan, Mohammed A. ; Azimi-Sadjadi, Mahmood R. ; Dobeck, Gerald J.
"This work was supported by the Office of Naval Research (ONR 321TS). The Technical Agent was Coastal Systems Station, Panama City, FL."
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.
Colorado State University. Libraries
1998
text ; image
application/pdf
ECEmra00044.pdf
FACFECEN100524ARTI
eng
c1998 IEEE