Bowhead whale localization using asynchronous hydrophones in the Chukchi Sea

Abstract

This paper estimates bowhead whale locations and uncertainties using non-linear Bayesian inversion of their modally-dispersed calls recorded on asynchronous recorders in the Chukchi Sea, Alaska. Bowhead calls were recorded on a cluster of 7 asynchronous ocean-bottom hydrophones that were separated by 0.5-9.2 km. A warping time-frequency analysis is used to extract relative mode arrival times as a function of frequency for nine frequency-modulated whale calls that dispersed in the shallow water environment. Each call was recorded on multiple hydrophones and the mode arrival times are inverted for: the whale location in the horizontal plane, source instantaneous frequency (IF), water sound-speed profile, seabed geoacoustic parameters, relative recorder clock drifts, and residual error standard deviations, all with estimated uncertainties. A simulation study shows that accurate prior environmental knowledge is not required for accurate localization as long as the inversion treats the environment as unknown. Joint inversion of multiple recorded calls is shown to substantially reduce uncertainties in location, source IF, and relative clock drift. Whale location uncertainties are estimated to be 30-160 m and relative clock drift uncertainties are 3-26 ms.

Nonlinear time-warping made simple: A step-by-step tutorial on underwater acoustic modal separation with a single hydrophone

“…Warping is thus perfectly adapted to the study of signals like those of baleen whale vocalizations in shallow water. It has notably been applied to localize bowhead whale calls in the Arctic (Bonnel et al, 2014;Warner et al, 2016), which are frequency modulated signals with an unknown TF law (and thus an unknown phase).…”

“…In particular, warping has been used to range baleen whales with a single sensor (Bonnel et al, 2014;Crance et al, 2015) and/or to estimate their calling depth . In the context where several non-synchronized hydrophones were available, warping has been used to estimate the latitude/ longitude position of marine mammals (Bonnel et al, 2008;Warner et al, 2016).…”

Trans-Dimensional Inversion of Modal Dispersion Data on the New England Mud Patch

“…Warping has been successfully applied in the past for modal filtering in a variety of scenarios [6], [7], [11], [16], [26], [27]. It has notably been used for geoacoustic/tomographic inversion using CSS [20] and J15 chirp data [8].…”

“…1) perform source deconvolution using (6) or phase compensation using (7), based on prior knowledge of source characteristics; 2) warp the signal using ( 10) and ( 11); 3) compute the spectrogram of the warped signal, and filter the (warped) modes using classical TF filtering; 4) unwarp the filtered modes; 5) estimate the group delay (or the instantaneous frequency) of each individual mode. This process has been used in the warping reference previously cited (see [6]- [8], [11], [16], [20], [26], [27]), and will thus not be detailed here.…”

“…Each frequency component of each mode travels with its own group speed, so that modal arrivals have frequency dependent travel times. Provided that these travel times can be estimated from the data, they can be used as input for inversion algorithms, to estimate source range [4]- [7], water sound-speed profile (SSP) [8], [9], and/or seabed geoacoustic properties [5], [9]- [12].…”