Cargando…
A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory
Bayesian methodology is a good way to infer unknown parameters in a marine environment. A passive source location method in a shallow water waveguide with a single sensor based on Bayesian theory is presented in this paper. The input of a Bayesian inversion algorithm is received different normal mod...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471741/ https://www.ncbi.nlm.nih.gov/pubmed/30934581 http://dx.doi.org/10.3390/s19061452 |
_version_ | 1783412093775511552 |
---|---|
author | Li, Xiaoman Piao, Shengchun Zhang, Minghui Liu, Yan |
author_facet | Li, Xiaoman Piao, Shengchun Zhang, Minghui Liu, Yan |
author_sort | Li, Xiaoman |
collection | PubMed |
description | Bayesian methodology is a good way to infer unknown parameters in a marine environment. A passive source location method in a shallow water waveguide with a single sensor based on Bayesian theory is presented in this paper. The input of a Bayesian inversion algorithm is received different normal mode impulse signals, which are separated and extracted with a warping transformation from received broadband impulse signals. The source range, depth, and other seabed parameters were estimated without prior knowledge of the seabed information. Different normal mode impulse acoustic signals travelling at different group speeds arrived at the sensor at different times because of the dispersion characteristics of the shallow water waveguide. The time delay of different modes can be used for the passive source location. However, normal mode group speeds are greatly affected by the environmental parameters. The performance of the passive location becomes negative when parameters mismatch. In this paper, the source location was transformed to the inversion of the source location and environmental parameters, which can be estimated accurately based on the multi-dimensional posterior probability density (PPD). This method is less limited by environmental factors, and the accuracy of inversion results can be analyzed according to the PPD of inversion parameters, which has higher reliability and a wider application scope. The effectiveness and robustness of the algorithm were quantified in terms of the root mean squared error (RMSE) at a variety of signal-to-noise ratios (SNRs) in 50 simulation sets. The RMSE values decreased with the SNR. The validity and accuracy of the method were proved by the results of simulation and experiment data. |
format | Online Article Text |
id | pubmed-6471741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64717412019-04-26 A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory Li, Xiaoman Piao, Shengchun Zhang, Minghui Liu, Yan Sensors (Basel) Article Bayesian methodology is a good way to infer unknown parameters in a marine environment. A passive source location method in a shallow water waveguide with a single sensor based on Bayesian theory is presented in this paper. The input of a Bayesian inversion algorithm is received different normal mode impulse signals, which are separated and extracted with a warping transformation from received broadband impulse signals. The source range, depth, and other seabed parameters were estimated without prior knowledge of the seabed information. Different normal mode impulse acoustic signals travelling at different group speeds arrived at the sensor at different times because of the dispersion characteristics of the shallow water waveguide. The time delay of different modes can be used for the passive source location. However, normal mode group speeds are greatly affected by the environmental parameters. The performance of the passive location becomes negative when parameters mismatch. In this paper, the source location was transformed to the inversion of the source location and environmental parameters, which can be estimated accurately based on the multi-dimensional posterior probability density (PPD). This method is less limited by environmental factors, and the accuracy of inversion results can be analyzed according to the PPD of inversion parameters, which has higher reliability and a wider application scope. The effectiveness and robustness of the algorithm were quantified in terms of the root mean squared error (RMSE) at a variety of signal-to-noise ratios (SNRs) in 50 simulation sets. The RMSE values decreased with the SNR. The validity and accuracy of the method were proved by the results of simulation and experiment data. MDPI 2019-03-25 /pmc/articles/PMC6471741/ /pubmed/30934581 http://dx.doi.org/10.3390/s19061452 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 Li, Xiaoman Piao, Shengchun Zhang, Minghui Liu, Yan A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory |
title | A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory |
title_full | A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory |
title_fullStr | A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory |
title_full_unstemmed | A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory |
title_short | A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory |
title_sort | passive source location method in a shallow water waveguide with a single sensor based on bayesian theory |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471741/ https://www.ncbi.nlm.nih.gov/pubmed/30934581 http://dx.doi.org/10.3390/s19061452 |
work_keys_str_mv | AT lixiaoman apassivesourcelocationmethodinashallowwaterwaveguidewithasinglesensorbasedonbayesiantheory AT piaoshengchun apassivesourcelocationmethodinashallowwaterwaveguidewithasinglesensorbasedonbayesiantheory AT zhangminghui apassivesourcelocationmethodinashallowwaterwaveguidewithasinglesensorbasedonbayesiantheory AT liuyan apassivesourcelocationmethodinashallowwaterwaveguidewithasinglesensorbasedonbayesiantheory AT lixiaoman passivesourcelocationmethodinashallowwaterwaveguidewithasinglesensorbasedonbayesiantheory AT piaoshengchun passivesourcelocationmethodinashallowwaterwaveguidewithasinglesensorbasedonbayesiantheory AT zhangminghui passivesourcelocationmethodinashallowwaterwaveguidewithasinglesensorbasedonbayesiantheory AT liuyan passivesourcelocationmethodinashallowwaterwaveguidewithasinglesensorbasedonbayesiantheory |