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Matched Field Processing: Ocean Experimental Data Analysis Using Feature Extraction Method  

Kim Kyung Seop (Dept. of Naval Architecture and Ocean Engineering, Seoul National University)
Seong Woo Jae (Dept. of Naval Architecture and Ocean Engineering, Seoul National University)
Song Hee Chun (Marine Physical Lab., UCSD)
Publication Information
The Journal of the Acoustical Society of Korea / v.24, no.1E, 2005 , pp. 21-27 More about this Journal
Abstract
Environmental mismatch has been one of important issues discussed in matched field processing for underwater source detection problem. To overcome this mismatch many algorithms professing robustness have been suggested. Feature extraction method (FEM) [Seong and Byun, IEEE Journal of Oceanic Engineering, 27(3), 642-652 (2002)] is one of robust matched field processing algorithms, which is based on the eigenvector estimation. Excluding eigenvectors of replica covariance matrix corresponding to large eigenvalues and forming an incoherent subspace of the replica field, the processor is formulated similarly to MUSIC algorithm. In this paper, by using the ocean experimental data, processing results of FEM and MVDR with white noise constraint (WNC) are presented for two levels of multi-tone source. Analysis of eigen-space of CSDM and FEM performance are also presented.
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