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...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 19; H. 6; S. 1452
Hauptverfasser:	Li, Xiaoman, Piao, Shengchun, Zhang, Minghui, Liu, Yan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 25.03.2019 MDPI
Schlagworte:	Accuracy Acoustics Bayesian methodology Decomposition Engineering Fourier transforms Genetic algorithms Global positioning systems GPS Laboratories Localization Methods passive location Propagation Sensors shallow water waveguide single sensor warping transformation China shallow water waveguide single sensor passive location Bayesian methodology warping transformation
ISSN:	1424-8220, 1424-8220
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Abstract	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.
AbstractList	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.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. 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.
Author	Liu, Yan Li, Xiaoman Piao, Shengchun Zhang, Minghui
AuthorAffiliation	1 Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China; lixiaoman@hrbeu.edu.cn (X.L.); zhangminghui@hrbeu.edu.cn (M.Z.); liuyan4996@hrbeu.edu.cn (Y.L.) 3 College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China 2 Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China
AuthorAffiliation_xml	– name: 3 College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China – name: 2 Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China – name: 1 Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China; lixiaoman@hrbeu.edu.cn (X.L.); zhangminghui@hrbeu.edu.cn (M.Z.); liuyan4996@hrbeu.edu.cn (Y.L.)
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Cites_doi	10.1063/1.2808704 10.1121/1.4883358 10.1121/1.3611395 10.1007/s11433-013-5243-x 10.1007/s11433-013-5359-z 10.1109/79.127284 10.1121/1.3664083 10.1121/1.4883370 10.1121/1.2918244 10.1109/21.286385 10.1109/JOE.1983.1145559 10.1088/0256-307X/28/11/114302 10.1142/S0218396X15500034 10.1121/1.4809678 10.1121/1.3459855 10.1155/2010/304103 10.1121/1.1419086 10.1109/TSP.2009.2013907
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Keywords	shallow water waveguide single sensor passive location Bayesian methodology warping transformation
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SubjectTerms	Accuracy Acoustics Bayesian methodology Decomposition Engineering Fourier transforms Genetic algorithms Global positioning systems GPS Laboratories Localization Methods passive location Propagation Sensors shallow water waveguide single sensor warping transformation
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Title	A Passive Source Location Method in a Shallow Water Waveguide with a Single Sensor Based on Bayesian Theory
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