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Underwater Noise Modeling and Direction-Finding Based on Heteroscedastic Time Series

EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 071528 (2006) Cite this article

Abstract

We propose a new method for practical non-Gaussian and nonstationary underwater noise modeling. This model is very useful for passive sonar in shallow waters. In this application, measurement of additive noise in natural environment and exhibits shows that noise can sometimes be significantly non-Gaussian and a time-varying feature especially in the variance. Therefore, signal processing algorithms such as direction-finding that is optimized for Gaussian noise may degrade significantly in this environment. Generalized autoregressive conditional heteroscedasticity (GARCH) models are suitable for heavy tailed PDFs and time-varying variances of stochastic process. We use a more realistic GARCH-based noise model in the maximum-likelihood approach for the estimation of direction-of-arrivals (DOAs) of impinging sources onto a linear array, and demonstrate using measured noise that this approach is feasible for the additive noise and direction finding in an underwater environment.

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Authors and Affiliations

  1. Department of Electrical Engineering, Amirkabir University of Technology, P.O. Box 15914, Tehran, Iran

    Hadi Amiri & Hamidreza Amindavar

  2. Department of Electrical and Computer Engineering, University of Tehran, P.O. Box 14395-515, Tehran, Iran

    Mahmoud Kamarei

Authors
  1. Hadi Amiri
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  2. Hamidreza Amindavar
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  3. Mahmoud Kamarei
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Correspondence to Hadi Amiri.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Amiri, H., Amindavar, H. & Kamarei, M. Underwater Noise Modeling and Direction-Finding Based on Heteroscedastic Time Series. EURASIP J. Adv. Signal Process. 2007, 071528 (2006). https://doi.org/10.1155/2007/71528

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