Sensing whales, storms, ships and earthquakes using an Arctic fibre optic cable.

Our oceans are critical to the health of our planet and its inhabitants. Increasing pressures on our marine environment are triggering an urgent need for continuous and comprehensive monitoring of the oceans and stressors, including anthropogenic activity. Current ocean observational systems are expensive and have limited temporal and spatial coverage.

Source level and vocalizing depth estimation of two blue whale subspecies in the western Indian Ocean from single sensor observations.

The source level (SL) and vocalizing source depth (SD) of individuals from two blue whale (BW) subspecies, an Antarctic blue whale (Balaenoptera musculus intermedia; ABW) and a Madagascar pygmy blue whale (Balaenoptera musculus brevicauda; MPBW) are estimated from a single bottom-mounted hydrophone in the western Indian Ocean. Stereotyped units (male) are automatically detected and the range is estimated from the time delay between the direct and lowest-order multiply-reflected acoustic paths (multipath-ranging). Allowing for geometric spreading and the Lloyd's mirror effect (range-, depth-, and frequency-dependent) SL and SD are estimated by minimizing the SL variance over a series of units from the same individual over time (and hence also range).

A performance comparison of tonal detectors for low-frequency vocalizations of Antarctic blue whales.

Extraction of tonal signals embedded in background noise is a crucial step before classification and separation of low-frequency sounds of baleen whales. This work reports results of comparing five tonal detectors, namely the instantaneous frequency estimator, YIN estimator, harmonic product spectrum, cost-function-based detector, and ridge detector. Comparisons, based on a low-frequency adaptation of the Silbido scoring feature, employ five metrics, which quantify the effectiveness of these detectors to retrieve tonal signals that have a wide range of signal to noise ratios (SNRs) and the quality of the detection results.

Passive stochastic matched filter for Antarctic blue whale call detection.

As a first step to Antarctic blue whale (ABW) monitoring using passive acoustics, a method based on the stochastic matched filter (SMF) is proposed. Derived from the matched filter (MF), this filter-based denoising method enhances stochastic signals embedded in an additive colored noise by maximizing its output signal to noise ratio (SNR). These assumptions are well adapted to the passive detection of ABW calls where emitted signals are modified by the unknown impulse response of the propagation channel.