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Bowhead whale localization using time-difference-of-arrival data from asynchronous recorders.

Graham A Warner1, Stan E Dosso1, David E Hannay2

  • 1School of Earth and Ocean Sciences, University of Victoria, 3800 Finnerty Road, Suite 405A, Victoria, British Columbia V8P 5C2, Canada.

The Journal of the Acoustical Society of America
|April 5, 2017
PubMed
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Accurate bowhead whale tracking is now possible using nonlinear Bayesian inversion of whale call arrival times. This method precisely estimates whale locations and hydrophone clock drifts in the Chukchi Sea.

Area of Science:

  • Marine bioacoustics
  • Oceanography
  • Signal processing

Background:

  • Bowhead whale vocalizations are crucial for population monitoring.
  • Accurate whale localization is challenging due to environmental factors and equipment limitations.
  • Previous localization methods using time-difference-of-arrival (TDOA) have limitations.

Purpose of the Study:

  • To develop and validate a nonlinear Bayesian inversion method for estimating bowhead whale locations and uncertainties.
  • To assess the feasibility of tracking migrating whales using acoustic data.
  • To improve the accuracy of underwater acoustic localization in complex environments.

Main Methods:

  • Deployment of a Y-shaped array of seven autonomous ocean-bottom hydrophones in the northeastern Chukchi Sea.

Related Experiment Videos

  • Manual association of hundreds of bowhead whale calls recorded over several months.
  • Calculation of time-difference-of-arrival (TDOA) using filtered waveform cross-correlations.
  • Application of nonlinear Bayesian inversion to estimate whale locations, hydrophone clock offsets, and sound speed, along with their uncertainties.

    • Main Results:

    • The nonlinear Bayesian inversion successfully estimated whale locations and hydrophone clock drifts.
    • Whale location uncertainties were sufficiently low for tracking migrating whales.
    • Estimated clock drift rates agreed with those obtained from ambient noise cross-correlations.
    • Linearized inversion methods failed to produce realistic results, highlighting the necessity of the nonlinear approach.

    Conclusions:

    • Nonlinear Bayesian inversion is a robust method for localizing bowhead whales and estimating system parameters.
    • The developed method enables accurate tracking of vocalizing whales, even with asynchronous hydrophone clocks.
    • This technique is suitable for analyzing large acoustic datasets for marine mammal research and conservation.