Sonar signal processing using probabilistic signal and ocean environmental models

Richard Lee Culver, H. John Camin

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Acoustic signals propagating through the ocean are refracted, scattered, and attenuated by the ocean volume and boundaries. Many aspects of how the ocean affects acoustic propagation are understood, such that the characteristics of a received signal can often be predicted with some degree of certainty. However, acoustic ocean parameters vary with time and location in a manner that is not, and cannot be, precisely known; some uncertainty will always remain. For this reason, the characteristics of the received signal can never be precisely predicted and must be described in probabilistic terms. A signal processing structure recently developed relies on knowledge of the ocean environment to predict the statistical characteristics of the received signal, and incorporates this description into the processor in order to detect and classify targets. Acoustic measurements at 250 Hz from the 1996 Strait of Gibraltar Acoustic Monitoring Experiment are used to illustrate how the processor utilizes environmental data to classify source depth and to underscore the importance of environmental model fidelity and completeness.

Original languageEnglish (US)
Pages (from-to)3619-3631
Number of pages13
JournalJournal of the Acoustical Society of America
Volume124
Issue number6
DOIs
StatePublished - Feb 18 2009

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sonar
signal processing
oceans
central processing units
acoustics
Gibraltar
acoustic propagation
straits
acoustic measurement
completeness
Acoustics
Ocean
Signal Processing

All Science Journal Classification (ASJC) codes

  • Arts and Humanities (miscellaneous)
  • Acoustics and Ultrasonics

Cite this

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Sonar signal processing using probabilistic signal and ocean environmental models. / Culver, Richard Lee; Camin, H. John.

In: Journal of the Acoustical Society of America, Vol. 124, No. 6, 18.02.2009, p. 3619-3631.

Research output: Contribution to journalArticle

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