Cargando…

A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance

A flight data recorder (FDR) is an electronic recording device placed in an aircraft for the purpose of facilitating the investigation of aviation accidents. If an aircraft crashes into water, an underwater locator beacon (ULB), which is installed on the FDR, is triggered by water immersion, and emi...

Descripción completa

Detalles Bibliográficos
Autores principales: Liang, Guolong, Wan, Guangming, Wang, Jinjin, Wang, Xue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085629/
https://www.ncbi.nlm.nih.gov/pubmed/32120939
http://dx.doi.org/10.3390/s20051292
_version_ 1783508975742877696
author Liang, Guolong
Wan, Guangming
Wang, Jinjin
Wang, Xue
author_facet Liang, Guolong
Wan, Guangming
Wang, Jinjin
Wang, Xue
author_sort Liang, Guolong
collection PubMed
description A flight data recorder (FDR) is an electronic recording device placed in an aircraft for the purpose of facilitating the investigation of aviation accidents. If an aircraft crashes into water, an underwater locator beacon (ULB), which is installed on the FDR, is triggered by water immersion, and emits an ultrasonic 10 ms pulse signal once per second at 37.5 kHz. This pulse signal can be detected by sonar equipment. However, the ULB signal only can be detectable 1–2 kilometers from the surface in normal conditions. Stochastic resonance (SR) is a rising theory in the field of weak signal detection. The classical stochastic resonance limits state that the input must be small-parameter and the sampling frequency must be 50 times higher than the signal frequency. It cannot be applied to the ULB signal detection. To resolve this problem, this paper presents a novel approach named mixing and normalizing stochastic resonance (MNSR). By mixing the ULB signal and normalizing SR system parameters, MNSR provides a new way to detect weak ULB signal. Meanwhile, we propose the parameters adjustment method of MNSR. We prove the effectiveness through numerical simulation. An experiment in a tank is employed to verify the practicability of this method.
format Online
Article
Text
id pubmed-7085629
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-70856292020-04-21 A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance Liang, Guolong Wan, Guangming Wang, Jinjin Wang, Xue Sensors (Basel) Article A flight data recorder (FDR) is an electronic recording device placed in an aircraft for the purpose of facilitating the investigation of aviation accidents. If an aircraft crashes into water, an underwater locator beacon (ULB), which is installed on the FDR, is triggered by water immersion, and emits an ultrasonic 10 ms pulse signal once per second at 37.5 kHz. This pulse signal can be detected by sonar equipment. However, the ULB signal only can be detectable 1–2 kilometers from the surface in normal conditions. Stochastic resonance (SR) is a rising theory in the field of weak signal detection. The classical stochastic resonance limits state that the input must be small-parameter and the sampling frequency must be 50 times higher than the signal frequency. It cannot be applied to the ULB signal detection. To resolve this problem, this paper presents a novel approach named mixing and normalizing stochastic resonance (MNSR). By mixing the ULB signal and normalizing SR system parameters, MNSR provides a new way to detect weak ULB signal. Meanwhile, we propose the parameters adjustment method of MNSR. We prove the effectiveness through numerical simulation. An experiment in a tank is employed to verify the practicability of this method. MDPI 2020-02-27 /pmc/articles/PMC7085629/ /pubmed/32120939 http://dx.doi.org/10.3390/s20051292 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liang, Guolong
Wan, Guangming
Wang, Jinjin
Wang, Xue
A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance
title A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance
title_full A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance
title_fullStr A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance
title_full_unstemmed A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance
title_short A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance
title_sort novel underwater location beacon signal detection method based on mixing and normalizing stochastic resonance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085629/
https://www.ncbi.nlm.nih.gov/pubmed/32120939
http://dx.doi.org/10.3390/s20051292
work_keys_str_mv AT liangguolong anovelunderwaterlocationbeaconsignaldetectionmethodbasedonmixingandnormalizingstochasticresonance
AT wanguangming anovelunderwaterlocationbeaconsignaldetectionmethodbasedonmixingandnormalizingstochasticresonance
AT wangjinjin anovelunderwaterlocationbeaconsignaldetectionmethodbasedonmixingandnormalizingstochasticresonance
AT wangxue anovelunderwaterlocationbeaconsignaldetectionmethodbasedonmixingandnormalizingstochasticresonance
AT liangguolong novelunderwaterlocationbeaconsignaldetectionmethodbasedonmixingandnormalizingstochasticresonance
AT wanguangming novelunderwaterlocationbeaconsignaldetectionmethodbasedonmixingandnormalizingstochasticresonance
AT wangjinjin novelunderwaterlocationbeaconsignaldetectionmethodbasedonmixingandnormalizingstochasticresonance
AT wangxue novelunderwaterlocationbeaconsignaldetectionmethodbasedonmixingandnormalizingstochasticresonance