An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound Emission

An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound Emission

Diver breathing sounds can be used as a characteristic for the passive detection of divers. This work introduces an approach for detecting the presence of a diver based on diver breathing sounds signals. An underwater channel model for passive diver detection is built to evaluate the impacts of acou...

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Bibliographic Details
Main Authors: Qiang Tu, Fei Yuan, Weidi Yang, En Cheng
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Journal of Marine Science and Engineering
Subjects:
underwater acoustic signal processing
channel model
signal enhancement
signal denoising
passive detection
Online Access:https://www.mdpi.com/2077-1312/8/1/44
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spelling doaj-9155f86088074c2b86d8ceb3dba68ec72021-04-02T14:53:40ZengMDPI AGJournal of Marine Science and Engineering2077-13122020-01-01814410.3390/jmse8010044jmse8010044An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound EmissionQiang Tu0Fei Yuan1Weidi Yang2En Cheng3Key Laboratory of Underwater Acoustic Communication and Marine Information Technology, Ministry of Education, Xiamen University, Xiamen 361005, ChinaKey Laboratory of Underwater Acoustic Communication and Marine Information Technology, Ministry of Education, Xiamen University, Xiamen 361005, ChinaCollege of Ocean and Earth Sciences, Xiamen University, Xiamen 361102, ChinaKey Laboratory of Underwater Acoustic Communication and Marine Information Technology, Ministry of Education, Xiamen University, Xiamen 361005, ChinaDiver breathing sounds can be used as a characteristic for the passive detection of divers. This work introduces an approach for detecting the presence of a diver based on diver breathing sounds signals. An underwater channel model for passive diver detection is built to evaluate the impacts of acoustic energy transmission loss and ambient noise interference. The noise components of the observed signals are suppressed by spectral subtraction based on block-based threshold theory and smooth minimal statistic noise tracking theory. Then the envelope spectrum features of the denoised signal are extracted for diver detection. The performance of the proposed detection method is demonstrated through experimental analysis and numerical modeling.https://www.mdpi.com/2077-1312/8/1/44underwater acoustic signal processingchannel modelsignal enhancementsignal denoisingpassive detection
collection DOAJ
language English
format Article
sources DOAJ
author Qiang Tu
Fei Yuan
Weidi Yang
En Cheng
spellingShingle Qiang Tu
Fei Yuan
Weidi Yang
En Cheng
An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound Emission
Journal of Marine Science and Engineering
underwater acoustic signal processing
channel model
signal enhancement
signal denoising
passive detection
author_facet Qiang Tu
Fei Yuan
Weidi Yang
En Cheng
author_sort Qiang Tu
title An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound Emission
title_short An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound Emission
title_full An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound Emission
title_fullStr An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound Emission
title_full_unstemmed An Approach for Diver Passive Detection Based on the Established Model of Breathing Sound Emission
title_sort approach for diver passive detection based on the established model of breathing sound emission
publisher MDPI AG
series Journal of Marine Science and Engineering
issn 2077-1312
publishDate 2020-01-01
description Diver breathing sounds can be used as a characteristic for the passive detection of divers. This work introduces an approach for detecting the presence of a diver based on diver breathing sounds signals. An underwater channel model for passive diver detection is built to evaluate the impacts of acoustic energy transmission loss and ambient noise interference. The noise components of the observed signals are suppressed by spectral subtraction based on block-based threshold theory and smooth minimal statistic noise tracking theory. Then the envelope spectrum features of the denoised signal are extracted for diver detection. The performance of the proposed detection method is demonstrated through experimental analysis and numerical modeling.
topic underwater acoustic signal processing
channel model
signal enhancement
signal denoising
passive detection
url https://www.mdpi.com/2077-1312/8/1/44
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