Parameter estimation of underwater impulsive noise with the Class B model

• Published in: IET radar, sonar & navigation Vol. 14; no. 7; pp. 1055 - 1060
• Main Authors: Zhang, Xuebo, Ying, Wenwei, Yang, Peixuan, Sun, Miao
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.07.2020
• Subjects: Class B modelled noise; Gaussian noise; Gaussian processes; impulse noise; least squares approximations; least‐square estimation method; Middleton Class B model; nonGaussian models; nonGaussian noise models; ocean ambient noise; parameter estimation; Research Article; shallow water; statistical analysis; underwater impulsive noise; underwater signal processors; underwater sound; least squares approximations; underwater sound; nonGaussian noise models; Class B modelled noise; ocean ambient noise; shallow water; Gaussian noise; Middleton Class B model; nonGaussian models; Gaussian processes; impulse noise; underwater impulsive noise; underwater signal processors; parameter estimation; statistical analysis; least-square estimation method
• ISSN: 1751-8784; 1751-8792
• DOI: 10.1049/iet-rsn.2019.0477

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.