This paper presents a novel blind statistical approach based on frequency singular value decomposition to separate seismic primary waves that are received on a linear array of three component antennas and enhance the SNR of the full multi-component seismic wavefield. Our proposed blind seismic separation algorithm consists of three main steps. Firstly, the frequency transformed multicomponent seismic wavefield data is rearranged into one long vector containing information on all frequencies and all component interactions. Secondly, the reduced dimensional spectral covariance matrix of the long vector data is estimated by means of singular value decomposition. Finally, the blind separation of the first primary wave is achieved by projecting the first eigenvector that has the highest eigenvalue of the covariance matrix onto the long data vector. The experimental results have shown that the proposed algorithm outperforms the conventional separation technique in terms of accuracy and complexity.
2nd Mosharaka International Conference on Communications, Propagation, and Electronics (MIC-CPE 2009)
Congress
2009 Global Congress on Communications, Propagation, and Electronics (GC-CPE 2009), 6-8 February 2009, Amman, Jordan
Pages
39-44
Topics
Antennas Analog Signal Processing
ISSN
2227-331X
DOI
BibTeX
@inproceedings{384CPE2009,
title={Blind Separation of Seismic Wavefield Recieved on Multicomponent Antenna using Frequency Singular Value Decomposition},
author={Aws K. Alqaisi, and , and },
booktitle={2009 Global Congress on Communications, Propagation, and Electronics (GC-CPE 2009)},
year={2009},
pages={39-44},
doi={}},
organization={Mosharaka for Research and Studies}
}
