Cargando…
Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor
Passive source localization is a challenging task for one receiver, and the pressure sensor provides relatively simple information. An ocean-bottom seismometer (OBS) sensor placed on the seafloor surface can provide more information—not only pressure information, but also three-axis (x-, y-, and z-a...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567348/ https://www.ncbi.nlm.nih.gov/pubmed/31091830 http://dx.doi.org/10.3390/s19102236 |
_version_ | 1783427056582787072 |
---|---|
author | Liu, Yaqin Zhang, Haigang Li, Ziyang Wang, Xiaohan Ma, Jun |
author_facet | Liu, Yaqin Zhang, Haigang Li, Ziyang Wang, Xiaohan Ma, Jun |
author_sort | Liu, Yaqin |
collection | PubMed |
description | Passive source localization is a challenging task for one receiver, and the pressure sensor provides relatively simple information. An ocean-bottom seismometer (OBS) sensor placed on the seafloor surface can provide more information—not only pressure information, but also three-axis (x-, y-, and z-axis) velocity information at the seafloor interface. In this paper, an OBS sensor was used to estimate the position of the broadband sound source in a Pekeris shallow water waveguide with elastic bottom. As the dynamics that characterize ocean acoustic applications are inherently nonlinear, non-Gaussian, and non-stationary processes that quickly vary with space and time, sequential Bayesian filtering, such as particle filtering (PF), is able to adapt to these environmental changes. Simulation results show that the PF method with the vertical wave impedance (the ratio of the pressure and vertical particle velocity) in the frequency domain as a measurement vector is not affected by source depth and source spectrum information, making it more tolerant and more robust than that with pressure in positioning. Experimental data results verified the effectiveness of the PF method with the vertical wave impedance for the localization of the explosive source. |
format | Online Article Text |
id | pubmed-6567348 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-65673482019-06-17 Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor Liu, Yaqin Zhang, Haigang Li, Ziyang Wang, Xiaohan Ma, Jun Sensors (Basel) Article Passive source localization is a challenging task for one receiver, and the pressure sensor provides relatively simple information. An ocean-bottom seismometer (OBS) sensor placed on the seafloor surface can provide more information—not only pressure information, but also three-axis (x-, y-, and z-axis) velocity information at the seafloor interface. In this paper, an OBS sensor was used to estimate the position of the broadband sound source in a Pekeris shallow water waveguide with elastic bottom. As the dynamics that characterize ocean acoustic applications are inherently nonlinear, non-Gaussian, and non-stationary processes that quickly vary with space and time, sequential Bayesian filtering, such as particle filtering (PF), is able to adapt to these environmental changes. Simulation results show that the PF method with the vertical wave impedance (the ratio of the pressure and vertical particle velocity) in the frequency domain as a measurement vector is not affected by source depth and source spectrum information, making it more tolerant and more robust than that with pressure in positioning. Experimental data results verified the effectiveness of the PF method with the vertical wave impedance for the localization of the explosive source. MDPI 2019-05-14 /pmc/articles/PMC6567348/ /pubmed/31091830 http://dx.doi.org/10.3390/s19102236 Text en © 2019 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 Liu, Yaqin Zhang, Haigang Li, Ziyang Wang, Xiaohan Ma, Jun Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor |
title | Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor |
title_full | Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor |
title_fullStr | Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor |
title_full_unstemmed | Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor |
title_short | Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor |
title_sort | particle filtering for localization of broadband sound source using an ocean-bottom seismometer sensor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567348/ https://www.ncbi.nlm.nih.gov/pubmed/31091830 http://dx.doi.org/10.3390/s19102236 |
work_keys_str_mv | AT liuyaqin particlefilteringforlocalizationofbroadbandsoundsourceusinganoceanbottomseismometersensor AT zhanghaigang particlefilteringforlocalizationofbroadbandsoundsourceusinganoceanbottomseismometersensor AT liziyang particlefilteringforlocalizationofbroadbandsoundsourceusinganoceanbottomseismometersensor AT wangxiaohan particlefilteringforlocalizationofbroadbandsoundsourceusinganoceanbottomseismometersensor AT majun particlefilteringforlocalizationofbroadbandsoundsourceusinganoceanbottomseismometersensor |