Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Extraction of acoustic normal mode depth functions using vertical line array data.

Tracianne B Neilsen1, Evan K Westwood

  • 1Applied Research Laboratories, The University of Texas at Austin, 78713-8029, USA.

The Journal of the Acoustical Society of America
|February 28, 2002
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Transfer learning to account for sound speed changes: Example for source ranging in underwater laboratory tank.

JASA express letters·2025
Same author

Introduction to the special issue on assessing sediment heterogeneity on continental shelves and slopesa).

The Journal of the Acoustical Society of America·2025
Same author

Ensemble approach to deep learning seabed classification using multichannel ship noisea).

The Journal of the Acoustical Society of America·2025
Same author

Deep sediment heterogeneity inferred using very low-frequency features from merchant shipsa).

The Journal of the Acoustical Society of America·2024
Same author

Information geometry analysis example for absolute and relative transmission loss in a shallow ocean.

JASA express letters·2024
Same author

Inference of source signatures of merchant ships in shallow ocean environmentsa).

The Journal of the Acoustical Society of America·2024
Same journal

High-resolution depth estimation for multiple wideband sources in deep sea via sparse Bayesian learninga).

The Journal of the Acoustical Society of America·2026
Same journal

Depression markers in speech: An approach based on tract variables dynamics.

The Journal of the Acoustical Society of America·2026
Same journal

The oyster toadfish (Opsanus tau) alters active and diurnal calling amid vessel noise in New York City.

The Journal of the Acoustical Society of America·2026
Same journal

Experimental noise characterisation of phase-locked tandem-rotor in edgewise flight.

The Journal of the Acoustical Society of America·2026
Same journal

The tune-text-temporal synergy: Prosodic effects of final segmental weakening in Neapolitan.

The Journal of the Acoustical Society of America·2026
Same journal

Monitoring vessel movement above critical offshore infrastructure using distributed acoustic sensing.

The Journal of the Acoustical Society of America·2026
See all related articles

This study presents a new method to extract acoustic normal modes in shallow oceans using sound data from a vertical line array (VLA). The technique successfully identifies acoustic modes from both continuous wave tones and ambient noise, even with changing ocean floor conditions.

Area of Science:

  • Ocean acoustics
  • Acoustic propagation modeling
  • Signal processing

Background:

  • Normal modes describe acoustic wave propagation in stratified media like the ocean.
  • Extracting these modes is crucial for understanding underwater sound behavior.
  • Previous methods faced challenges with complex ocean environments.

Purpose of the Study:

  • To develop and validate a novel method for extracting acoustic normal modes from shallow ocean sound recordings.
  • To assess the method's effectiveness under varying environmental conditions and with different sound sources.
  • To demonstrate the applicability of the technique to both active (cw tones) and passive (ambient noise) acoustic data.

Main Methods:

  • Singular Value Decomposition (SVD) applied to frequency-specific cross-spectral density matrices.

Related Experiment Videos

  • Utilizing data from a vertical line array (VLA) of hydrophones.
  • Analysis of temporally averaged spatial cross-spectral density.

    • Main Results:

    • Successfully extracted depth-dependent normal modes and their properties (excitations, eigenvalues).
    • Demonstrated successful mode extraction from continuous wave (cw) tones under range-independent and range-dependent (up-slope) bathymetry.
    • Validated the method's effectiveness with ambient noise across multiple frequencies.
    • Identified key conditions for successful mode extraction: sufficient VLA depth sampling, source-VLA range sampling, and source travel distance.

    Conclusions:

    • The SVD-based method is effective for extracting acoustic normal modes in shallow ocean environments.
    • The technique is robust, working with both controlled signals and ambient noise.
    • Successful application to real-world data from the Area Characterization Test II validates the method's practical utility.