Abstract:

Many species of marine mammals live in socially organized groups and exhibit cohesive behavior. Since acoustics is their primary communication tool, it has been suggested that acoustic signal characteristics and emission patterns carry attributes of individuals among the group. A dynamic approach for rhythmic analysis of echolocation and communication signals is presented. The algorithm provides detection of a particular species in a continuous stream of broadband acoustic data and a robust (to low signal‐to‐noise ratio) method for association of rhythmic frequencies with individuals. The method is applied to passive acoustic recordings collected by the Littoral Acoustic Demonstration Center (LADC). The efficacy of the method for sperm whale echolocation clicks and codas, and beaked whale clicks is addressed. The algorithm is a part of an integrated tool proposed by LADC for identification of individual animals in a group. In parallel, multi‐attribute similarity analysis and source localization are applied to the same volume of data. The results are integrated and compared to provide reliable identification. The proposed approach is beneficial for passive acoustic studies of marine species population and social behavior and may contribute to understanding acoustic communication among marine mammals. [Research supported by the Louisiana Optical Network Initiative, ONR, and SPAWAR.]