Three-dimensional localization of sperm whales using a single hydrophone

Tiemann, Christopher O.; Thode, Aaron; Straley, Janice M.; O'Connell, Victoria; Folkert, Kendall

doi:10.1121/1.2335577

Cited by 75 publications

(58 citation statements)

References 35 publications

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“…Nevertheless, the same localization principle as in [4] can be applied to the clustered (unresolved) multipath arrival patterns. The localization algorithm can be decomposed into two steps.…”

Section: Theory and Proceduresmentioning

confidence: 99%

“…In the present work the signals considered for localization are not short-duration clicks like in [4], but rather frequencymodulated (FM) signals emitted by distant sources, so that the arrival pattern can only be resolved into clusters of overlapping individual arrivals. Nevertheless, the same localization principle as in [4] can be applied to the clustered (unresolved) multipath arrival patterns.…”

Section: Theory and Proceduresmentioning

confidence: 99%

“…Tiemann et al [4] used sperm whale click multipath arrival patterns to locate the whale with a single receiver, comparing the detected click arrival pattern with predicted arrival patterns from candidate sources to estimate the best match. Thanks to the bathymetric variability in the area, the source (sperm whale) could be localized in the 3D space (range, depth, azimuth) around the receiver.…”

Section: Theory and Proceduresmentioning

confidence: 99%

“…The feasibility of using a single receiver for range and depth estimation has been demonstrated in ray theory ( [1], [2], [3]). While 3D (range, depth, azimuth) localization usually requires a vertical or horizontal array, more recent work has demonstrated its feasibility with a single receiver by using azimuth-dependent bathymetric information for bearing estimation [4]. Reference [4] uses sperm whale click multipath arrival patterns to locate the whale with a single receiver, by comparing the detected click arrival pattern to predicted arrival patterns from candidate sources to estimate the best match.…”

Section: Introductionmentioning

confidence: 99%

“…While 3D (range, depth, azimuth) localization usually requires a vertical or horizontal array, more recent work has demonstrated its feasibility with a single receiver by using azimuth-dependent bathymetric information for bearing estimation [4]. Reference [4] uses sperm whale click multipath arrival patterns to locate the whale with a single receiver, by comparing the detected click arrival pattern to predicted arrival patterns from candidate sources to estimate the best match. Thanks to the diverse bathymetric information in the area, the localization of the sperm whale could be done in 3D space around the receiver.…”

Section: Introductionmentioning

confidence: 99%

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3D source location using overlapping multipath propagation

Barazzutti¹,

Seger

Thode

et al. 2017

OCEANS 2017 - Aberdeen

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Abstract-In passive acoustic monitoring, source localization using multipath propagation can be challenging whenever the source-receiver configuration leads to overlapping multipath arrival patterns. We propose a single-hydrophone model-based method with matched-impulse response (IR) processing that exploits unresolved multipath arrival patterns to locate the source in 3D, making the best use of the bathymetric information as well as the time differences of groups of arrivals. When only groups of paths are resolved, the identity of the paths constituting the groups remains unknown, preventing the use of classical localization methods. To overcome this critical limitation, we apply an approach based on the characterization of groups of paths to estimate the source location.

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Section: Theory and Proceduresmentioning

confidence: 99%

Section: Theory and Proceduresmentioning

confidence: 99%

Section: Theory and Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

3D source location using overlapping multipath propagation

Barazzutti¹,

Seger

Thode

et al. 2017

OCEANS 2017 - Aberdeen

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Acoustic localization of terrestrial wildlife: Current practices and future opportunities

Rhinehart

Chronister

Devlin

et al. 2020

Ecology and Evolution

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Autonomous acoustic recorders are an increasingly popular method for low‐disturbance, large‐scale monitoring of sound‐producing animals, such as birds, anurans, bats, and other mammals. A specialized use of autonomous recording units (ARUs) is acoustic localization, in which a vocalizing animal is located spatially, usually by quantifying the time delay of arrival of its sound at an array of time‐synchronized microphones. To describe trends in the literature, identify considerations for field biologists who wish to use these systems, and suggest advancements that will improve the field of acoustic localization, we comprehensively review published applications of wildlife localization in terrestrial environments. We describe the wide variety of methods used to complete the five steps of acoustic localization: (1) define the research question, (2) obtain or build a time‐synchronizing microphone array, (3) deploy the array to record sounds in the field, (4) process recordings captured in the field, and (5) determine animal location using position estimation algorithms. We find eight general purposes in ecology and animal behavior for localization systems: assessing individual animals' positions or movements, localizing multiple individuals simultaneously to study their interactions, determining animals' individual identities, quantifying sound amplitude or directionality, selecting subsets of sounds for further acoustic analysis, calculating species abundance, inferring territory boundaries or habitat use, and separating animal sounds from background noise to improve species classification. We find that the labor‐intensive steps of processing recordings and estimating animal positions have not yet been automated. In the near future, we expect that increased availability of recording hardware, development of automated and open‐source localization software, and improvement of automated sound classification algorithms will broaden the use of acoustic localization. With these three advances, ecologists will be better able to embrace acoustic localization, enabling low‐disturbance, large‐scale collection of animal position data.

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