A Geometric Calibration Method of Hydrophone Array Based on Maximum Likelihood Estimation with Sources in Near Field

Considering the requirement of the near-field calibration under strong underwater multipath condition, a high-precision geometric calibration method based on maximum likelihood estimation is proposed. It can be used as both auxiliary-calibration and self-calibration. According to the near-field geom...

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Vydané v:	Journal of marine science and engineering Ročník 8; číslo 9; s. 678
Hlavní autori:	Zou, Nan, Jia, Zhenqi, Fu, Jin, Feng, Jia, Liu, Mengqi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.09.2020
Predmet:	Accuracy Acoustics Algorithms Calibration Computer simulation correlated multipath channel Differential geometry Eigenvectors element position error Evolutionary computation Geometry Hydrophones lake experiment long hydrophone array Mathematical research Maximum likelihood estimation Maximum likelihood estimators Methods Noise Objective function Optimization optimization solution Optimization theory Parameter estimation Self calibration Signal to noise ratio Simulation unconditioned maximum likelihood detector (UML) China
ISSN:	2077-1312, 2077-1312
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Abstract	Considering the requirement of the near-field calibration under strong underwater multipath condition, a high-precision geometric calibration method based on maximum likelihood estimation is proposed. It can be used as both auxiliary-calibration and self-calibration. According to the near-field geometry error model, the objective function of nonlinear optimization problem is constructed by using the unconditional maximum likelihood estimator. The influence of multipath on geometric calibration is studied. The strong reflections are considered as the coherent sources, and the compensation strategy for auxiliary-calibration is realized. The optimization method (differential evolution, DE) is used to solve the geometry errors and sources’ position. The method in this paper is compared with the eigenvector method. The simulation results show that the method in this paper is more accurate than the eigenvector method especially under high signal-to-noise ratio (SNR) and multipath environment. Experiment results further verify the effectiveness.
AbstractList	Considering the requirement of the near-field calibration under strong underwater multipath condition, a high-precision geometric calibration method based on maximum likelihood estimation is proposed. It can be used as both auxiliary-calibration and self-calibration. According to the near-field geometry error model, the objective function of nonlinear optimization problem is constructed by using the unconditional maximum likelihood estimator. The influence of multipath on geometric calibration is studied. The strong reflections are considered as the coherent sources, and the compensation strategy for auxiliary-calibration is realized. The optimization method (differential evolution, DE) is used to solve the geometry errors and sources’ position. The method in this paper is compared with the eigenvector method. The simulation results show that the method in this paper is more accurate than the eigenvector method especially under high signal-to-noise ratio (SNR) and multipath environment. Experiment results further verify the effectiveness. Considering the requirement of the near-field calibration under strong underwater multipath condition, a high-precision geometric calibration method based on maximum likelihood estimation is proposed. It can be used as both auxiliary-calibration and self-calibration. According to the near-field geometry error model, the objective function of nonlinear optimization problem is constructed by using the unconditional maximum likelihood estimator. The influence of multipath on geometric calibration is studied. The strong reflections are considered as the coherent sources, and the compensation strategy for auxiliary-calibration is realized. The optimization method (differential evolution, DE) is used to solve the geometry errors and sources' position. The method in this paper is compared with the eigenvector method. The simulation results show that the method in this paper is more accurate than the eigenvector method especially under high signal-to-noise ratio (SNR) and multipath environment. Experiment results further verify the effectiveness. Keywords: long hydrophone array; element position error; unconditioned maximum likelihood detector (UML); correlated multipath channel; optimization solution; lake experiment
Audience	Academic
Author	Fu, Jin Liu, Mengqi Jia, Zhenqi Zou, Nan Feng, Jia
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SubjectTerms	Accuracy Acoustics Algorithms Calibration Computer simulation correlated multipath channel Differential geometry Eigenvectors element position error Evolutionary computation Geometry Hydrophones lake experiment long hydrophone array Mathematical research Maximum likelihood estimation Maximum likelihood estimators Methods Noise Objective function Optimization optimization solution Optimization theory Parameter estimation Self calibration Signal to noise ratio Simulation unconditioned maximum likelihood detector (UML)
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Title	A Geometric Calibration Method of Hydrophone Array Based on Maximum Likelihood Estimation with Sources in Near Field
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