NDLI: Parameter estimation of underwater impulsive noise with the Class B model

Content Provider	IET Digital Library
Author	Zhang, Xuebo Ying, Wenwei Yang, Peixuan Sun, Miao
Abstract	The statistical characteristic of ocean ambient noise plays an important role in developing underwater signal processors. Considering that the noise in shallow water shows the impulsive nature, non-Gaussian noise models are usually applied to model the ocean ambient noise. In this study, the ocean ambient noise is modelled by using the Middleton Class B model, which can be decomposed into Gaussian and non-Gaussian models. Then, the parameters of Class B model are estimated based on the least-square estimation method, which can be deduced by using the characteristic function of the Middleton Class B model. The processing results of simulated data and real data indicate that the presented method well estimates the parameters of Class B modelled noise. Besides, it further shows that the Middleton Class B model is suitable for modelling the impulsive noise in shallow water.
Starting Page	1055
Ending Page	1060
Page Count	6
ISSN	17518784
Volume Number	14
e-ISSN	17518792
Issue Number	Issue 7, Jul (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/14/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2019.0477
Journal	IET Radar, Sonar & Navigation
Publisher Date	2020-03-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Class B Modelled Noise Gaussian Noise Gaussian Processes Impulse Noise Interpolation And Function Approximation Least Squares Approximation Least-square Estimation Method Middleton Class B Model NonGaussian Model NonGaussian Noise Model Numerical Analysis Ocean Ambient Noise Parameter Estimation Probability Theory Shallow Water Statistical Analysis Statistics Stochastic Linearised SCUC Underwater Impulsive Noise Underwater Signal Processors Underwater Sound
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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