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Introduction to Underwater Acoustic Signal Processing

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Underwater Acoustic Signal Processing

Part of the book series: Modern Acoustics and Signal Processing ((MASP))

Abstract

The topic of this book is the theory and application of signal processing in underwater acoustics. The majority of applications in underwater acoustics can be described as remote sensing where an electro-mechanical system exploits acoustic signals underwater to perform inference related to an object of interest. The most recognized application is sonar (sound only navigation and ranging) for which the stated purpose is navigation and ranging (i.e., determining the distance or range from the sonar platform to an object of interest). The techniques by which underwater measurements of acoustic pressure are converted into navigation and ranging information are what comprise the signal-processing component of a sonar system. In this chapter, underwater acoustic signal processing is introduced according to the more general detection, classification, localization, and tracking (DCLT) paradigm. Common applications of underwater acoustic signal processing are described along with specific examples of signals of interest and each of the topics in the DCLT paradigm. The chapter is concluded with an explanation of how this book is organized, who the intended audience is, and how it might be used.

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Notes

  1. 1.

    The choice of the adjective acoustic or acoustical is made following the paradigm of [2].

  2. 2.

    Acknowledgement: CTBTO [6] with gratitude to Drs. G. Haralabus, M. Zampolli, P. Nielsen, and A. Brouwer for their assistance in identifying, accessing, and interpreting the data.

  3. 3.

    Acknowledgement: CTBTO [6] with gratitude to Drs. G. Haralabus, M. Zampolli, P. Nielsen, and A. Brouwer for their assistance in identifying, accessing, and interpreting the data.

  4. 4.

    Acknowledgement: NURC Clutter JRP [12] with gratitude to Dr. P. Nielsen (scientist in charge, Clutter 2007 Experiment) and Dr. C. Holland (ARL/PSU) who led this particular investigation.

  5. 5.

    Acknowledgment with gratitude to Prof. S. Parks, Biology Dept., Syracuse University, who acquired the data under funding from the National Oceanic and Atmospheric Administration (NOAA) and a Department of Fisheries and Oceans (DFO) Canada permit.

  6. 6.

    Acknowledgement: NURC Clutter JRP [12] with gratitude to Dr. P. Nielsen (scientist in charge, Clutter 2007 Experiment).

  7. 7.

    Acknowledgement: NURC Clutter JRP [12] with gratitude to Dr. P. Nielsen (scientist in charge, Clutter 2009 Experiment) and Dr. P. Hines, Mr. J. Scrutton, and Mr. S. Murphy (DRDC) who designed and led this particular investigation, collated and labeled the echoes.

  8. 8.

    Acknowledgement: NURC Clutter JRP [12] with gratitude to Dr. P. Nielsen (scientist in charge, Clutter 2007 Experiment).

  9. 9.

    More properly, a conical angle is estimated. The bearing is obtained, subject to a left/right ambiguity, by assuming the line array is horizontal and restricting the solution to the horizontal plane.

  10. 10.

    Acknowledgement: NURC Clutter JRP [12] with gratitude to Dr. P. Nielsen (scientist in charge, Clutter 2009 Experiment) and Dr. P. Hines, Mr. J. Scrutton, and Mr. S. Murphy (DRDC) who designed and led this particular investigation, collated and labeled the echoes.

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Authors and Affiliations

  1. Ellicott City, MD, USA

    Douglas A. Abraham

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  1. Douglas A. Abraham
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Abraham, D.A. (2019). Introduction to Underwater Acoustic Signal Processing. In: Underwater Acoustic Signal Processing. Modern Acoustics and Signal Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-92983-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-92983-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92981-1

  • Online ISBN: 978-3-319-92983-5

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