Examining the impact of the ocean environment on cetacean classification using theocean acoustics and seismic exploration synthesis (OASES) propagation model

Passive acoustic monitoring (PAM) is now in wide use to study cetaceans in their natural habitats. Since cetaceans can be found in all ocean basins, their habitats cover diverse underwater environments. Properties of the ocean environment such as the sound speed profile, bathymetry, and sediment properties can be markedly different between these diverse environments. This leads to differences in how a cetacean vocalization is distorted by propagation effects and may impact the accuracy of PAM systems. To develop an automatic PAM system capable of operating effectively under numerous environmental conditions one must understand how propagation conditions affect these systems. Previous effort using a relatively limited data set has shown that a prototype aural classifier developed at Defence R&D Canada can be used to reduce false alarm rates and successfully discriminate cetacean vocalizations from several species. The aural classifier achieves accurate results by using perceptual signal features that model the features employed by the human auditory system. The current work uses the OASES pulse propagation model to examine the robustness of the classifier under various environmental conditions; preliminary results will be presented from cetacean vocalizations that were transmitted over several ranges through environments modeled using conditions measured during experimental trials.