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Research project: Tracking sperm whales with particle filters

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Passive acoustics provide a powerful took for detecting, identifying and tracking cetaceans. Much of the acoustic research methods were pioneered in sperm whale (Physeter macrocephalus) due to the impulsive nature and high sound pressure levels of the vocalisations (~220 dB re: 1µPa) making them relatively easy to detect. The most prevalent hydrophone configuration used in acoustic based studies consists of a hydrophone element pair towed behind a boat or ship.

Project Overview

Passive acoustics provide a powerful took for detecting, identifying and tracking cetaceans. Much of the acoustic research methods were pioneered in sperm whale (Physeter macrocephalus) due to the impulsive nature and high sound pressure levels of the vocalisations (~220 dB re: 1µPa) making them relatively easy to detect. The most prevalent hydrophone configuration used in acoustic based studies consists of a hydrophone element pair towed behind a boat or ship. Cross-correlation of the signals received by each element provides a measurement of delay of the sound arriving on one element in relation to the arrival of the sound at the other element. Typically this measurement is treated as an estimate of the animal’s bearing relative to the array aperture. The nature of this kind of measurement results in a hyperbolic ambiguity surface centred between the two elements so it is unknown whether the inferred bearing to the animal is to the left, the right, below or anywhere in-between. Furthermore the time delay alone provides no information regarding the animal’s range or, in the case of multiple vocalising animals, which animal the vocalisation came from.

It is proposed that tracking filters can play a role in overcoming the limitations of the measurement process. Firstly a Multiple Hypothesis Tracking (MHT), based on the Kalman filter, is utilised to associate a vocalisation with an animal. Secondly combining motion data from the hydrophone elements and known statistics about the animal’s motion it is proposed that a Bayesian estimate of the animal’s azimuth, elevation and range can be obtained using a Sampling Importance Re-Sampling (SIR) particle filter. The tracking algorithms are demonstrated on sperm whale vocalisations, due to the readily available data and the ease detection and identification, but could be applied to any of the great whales given appropriate detection and time delay extraction algorithms.

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