Single-hydrophone model-based passive sonar source depth classification

Colin W. Jemmott; R. Lee Culver

doi:10.1109/JOE.2011.2162375

Single-hydrophone model-based passive sonar source depth classification

Colin W. Jemmott, R. Lee Culver

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

This paper introduces a source depth classification technique applicable to passive low-frequency narrowband sonar signals received by a single hydrophone in shallow water. The classifier is based upon Rice probability density functions with model-derived parameters for the received amplitude of a tonal signal that has been modulated by propagation through the ocean. Differences in modal excitation due to source depth result in different probability density functions of received amplitude that allow for source depth classification. The performance of the technique is demonstrated using data from the SWellEx-96 experiment.

Original language	English (US)
Article number	6015498
Pages (from-to)	696-702
Number of pages	7
Journal	IEEE Journal of Oceanic Engineering
Volume	36
Issue number	4
DOIs	https://doi.org/10.1109/JOE.2011.2162375
State	Published - Oct 2011

All Science Journal Classification (ASJC) codes

Ocean Engineering
Mechanical Engineering
Electrical and Electronic Engineering

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10.1109/JOE.2011.2162375

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title = "Single-hydrophone model-based passive sonar source depth classification",

abstract = "This paper introduces a source depth classification technique applicable to passive low-frequency narrowband sonar signals received by a single hydrophone in shallow water. The classifier is based upon Rice probability density functions with model-derived parameters for the received amplitude of a tonal signal that has been modulated by propagation through the ocean. Differences in modal excitation due to source depth result in different probability density functions of received amplitude that allow for source depth classification. The performance of the technique is demonstrated using data from the SWellEx-96 experiment.",

author = "Jemmott, \{Colin W.\} and Culver, \{R. Lee\}",

note = "Funding Information: Manuscript received August 19, 2009; revised December 10, 2010; accepted July 11, 2011. Date of publication September 08, 2011; date of current version October 21, 2011. This work was supported by the U.S. Office of Naval Research Undersea Signal Processing, Code 321US. Associate Editor: D. Knobles. C. W. Jemmott is with Applied Operations Research, Solana Beach, CA 92075 USA (e-mail: [email protected]). R. L. Culver is with the Applied Research Laboratory, The Pennsylvania State University, State College, PA 16801 USA (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JOE.2011.2162375",

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doi = "10.1109/JOE.2011.2162375",

language = "English (US)",

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journal = "IEEE Journal of Oceanic Engineering",

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AU - Culver, R. Lee

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N2 - This paper introduces a source depth classification technique applicable to passive low-frequency narrowband sonar signals received by a single hydrophone in shallow water. The classifier is based upon Rice probability density functions with model-derived parameters for the received amplitude of a tonal signal that has been modulated by propagation through the ocean. Differences in modal excitation due to source depth result in different probability density functions of received amplitude that allow for source depth classification. The performance of the technique is demonstrated using data from the SWellEx-96 experiment.

AB - This paper introduces a source depth classification technique applicable to passive low-frequency narrowband sonar signals received by a single hydrophone in shallow water. The classifier is based upon Rice probability density functions with model-derived parameters for the received amplitude of a tonal signal that has been modulated by propagation through the ocean. Differences in modal excitation due to source depth result in different probability density functions of received amplitude that allow for source depth classification. The performance of the technique is demonstrated using data from the SWellEx-96 experiment.

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Single-hydrophone model-based passive sonar source depth classification

Abstract

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