Literature DB >> 27908045

Source depth discrimination with a vertical line array.

Ewen Conan1, Julien Bonnel1, Thierry Chonavel2, Barbara Nicolas3.   

Abstract

Source depth estimation with a vertical line array generally involves mode filtering, then matched-mode processing. Because mode filtering is an ill-posed problem if the water column is not well-sampled, concerns for robustness motivate a simpler approach: source depth discrimination considered as a binary classification problem. It aims to evaluate whether the source is near the surface or submerged. These two hypotheses are formulated in terms of normal modes, using the concept of trapped and free modes. Decision metrics based on classic mode filters are proposed. Monte Carlo methods are used to predict performance and set the parameters of a classifier accordingly.

Entities:  

Year:  2016        PMID: 27908045     DOI: 10.1121/1.4967506

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  2 in total

1.  Acoustic Classification of Surface and Underwater Vessels in the Ocean Using Supervised Machine Learning.

Authors:  Jongkwon Choi; Youngmin Choo; Keunhwa Lee
Journal:  Sensors (Basel)       Date:  2019-08-09       Impact factor: 3.576

2.  Depth Discrimination for Low-Frequency Sources Using a Horizontal Line Array of Acoustic Vector Sensors Based on Mode Extraction.

Authors:  Guolong Liang; Yifeng Zhang; Guangpu Zhang; Jia Feng; Ce Zheng
Journal:  Sensors (Basel)       Date:  2018-10-30       Impact factor: 3.576

  2 in total

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