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Matched Field Processing: Ocean Experimental Data Analysis Using Feature Extraction Method
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  • Matched Field Processing: Ocean Experimental Data Analysis Using Feature Extraction Method
  • Matched Field Processing: Ocean Experimental Data Analysis Using Feature Extraction Method
저자명
Kim. Kyung Seop,Seong. Woo Jae,Song. Hee Chun
간행물명
The journal of the Acoustical Society of Korea
권/호정보
2005년|24권 |pp.21-27 (7 pages)
발행정보
한국음향학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

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.