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The Littoral Acoustic Demonstration Center (LADC) acquired underwater acoustic data from clicking sperm and beaked whales in the Gulf of Mexico during an experiment in July 2007. Analysis of sperm whale echolocation and coda clicks in the data has been presented at previous ASA meetings. Research emphasis is now on identifying individual beaked whales from their echolocation clicks. Again, clustering methods present one appropriate approach to the automated identification of these whales by computer. Self‐organizing maps have the ability to limit the number of clusters automatically, and their successful use with sperm whales encourages the application to beaked whales as well. Results for time, frequency, and wavelet domain data allow comparison among clustering done using different signal representations and help highlight areas of concern in the analysis. As in the case of sperm whales, the beaked whale identifications are verified by comparing to cadence analysis (as presented in an accompanying abstract) and to a limited extent by manual analysis and localization. [Research supported by ONR and SPAWAR.]

Previous research to identify individual sperm and beaked whales from the properties of their echolocation and coda clicks using cluster analysis has been reported. Although reasonably consistent and robust results showing distinct classes (each corresponding to an individual) have been obtained with both self‐organizing maps and K‐means, no independent verification of these identifications has previously been available. However, data from a July 2007 experiment in the Gulf of Mexico should provide enough geometry information to verify some identifications. The Littoral Acoustic Demonstration Center deployed six environmental acoustic recording system buoys, measuring to 96 kHz for 9 days, to record sperm and beaked whale clicks in the northern Gulf of Mexico. Three buoys were in close proximity to enable multisensor detections of single clicks for possible localization, tracking, or bearing estimation sufficient to confirm the identification of individuals from cluster analysis. Displays of cluster class...

EARS buoys were developed as autonomous, moored, underwater recording systems by the Naval Oceanographic Office (NAVOCEANO) to make long‐term ocean ambient noise measurements. When the Littoral Acoustic Demonstration Center (LADC) was formed as a consortium of university and U.S. Navy scientists in 2001, the buoys were capable of measuring up to 1000 Hz for 1 yr. LADC added listening to sperm whales to its noise and propagation measurements. NAVOCEANO quickly modified the buoys to measure up to 5859 Hz for 36 days. The buoys, moored at depths from 550 to 950 m in the Gulf of Mexico, produced exceptionally clear recordings of sperm whale echolocation and coda clicks and recordings of other whales. EARS Generation 2 buoys are now capable of recording one channel to 96 kHz, or four channels to 25 kHz, for more than 13 days on four 120 Gbyte notebook disk drives. Experiments in the Gulf of Mexico and the Ligurian Sea have targeted both sperm and beaked whales. Audio results and visualizations of these recordings reveal rich detail of Odontocete clicks and enable new analyses, such as the identification of individual whales from the properties of their clicks. [Research supported by ONR and SPAWAR.]

It has been observed that clicks within a single sperm whale coda have similar time and frequency properties, but these properties can differ from one coda to the next. Thus, it may be possible to identify individual sperm whales acoustically from the properties of their coda clicks. While sorting the codas by eye is promising, there is an obvious need to have automated identification by computer. Clustering methods present one appropriate approach to the identification of individuals. Although both K‐means and self‐organizing maps have been applied, the advantage of the latter, i.e., the ability to limit the number of clusters automatically, has favored its use. More recently, differences in echolocation clicks have become the basis of possible acoustic identification of individuals, also. Experiments by the Littoral Acoustic Demonstration Center in 2001, 2002, and 2007 as well as Detection, Classification, and Localization Workshop data have enabled extensive testing of these ideas. Results of the clustering for both types of clicks are encouraging. Localization and echolocation click rhythms have been used to verify the clusters. The identification has been extended to echolocation clicks of beaked whales. Illustrative results are presented. [Research supported by ONR and SPAWAR.]

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 applie...