| Título: | Detection and classification of North Atlantic right whales in the bay of fundy using independent component analysis |
| Autores: |
La Cour, Brian R.; Applied Research Laboratories, University of Texas at Austin, P.O. Box 8029, Austin, TX 78713 Linford, Michael A.; Applied Research Laboratories, University of Texas at Austin, P.O. Box 8029, Austin, TX 78713 |
| Fecha: | 2004-06-01 |
| Publicador: | Canadian Acoustics |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Conference Proceedings Actes de congrès |
| Tema: |
Marine biology Algorithms; Automation; Data acquisition; Fish detectors; Gaussian noise (electronic); Hydrophones; Independent component analysis; Parameter estimation; Probability; Problem solving; Real time systems; Submarines; Acoustic automated detection; Multiple sound sources; Non-Gaussian signals; Vocalization |
| Descripción: |
A novel method of detection and classification for marine mammals is presented which uses techniques from independent component analysis to solve the blind source separation problem for North Atlantic right whales (Eubalaena glacialis). Using the fundamentally non-Gaussian nature of marine mammal vocalizations and data collected on multiple hydrophones, we are able to separate right whale source spectra, up to an unknown scale, from ambient noise. This technique assumes that the array data is a linear combination of non-Gaussian source signals but does not require specific knowledge of the array geometry. A detection algorithm which separates right whale vocalizations from ambient background using a Kolmogorov-Smirnov test statistic is presented and tested on data collected in the Bay of Fundy. The performance of the detector was found to be such that it was possible to achieve a probability of detection of about three-fourths with a false alarm probability of about one-third. Independent component analysis was found to provide little improvement over standard principle component analysis, which was used as preprocessing step. Une nouvelle methode de detection et de classification pour les mammifères marins est presentee. Elle utilise des techniques d’analyse par composantes independantes pour résoudre des problemes de separation aveugle de sources pour des baleines franches de l’Atlantique Nord (Eubalaena glacialis). En se basant sur la nature non gaussienne des vocalisations des mammiferes marins et sur les donnees recueillies par un ensemble d’hydrophones, nous avons ete capables de separer les spectres de baleines franches, jusqu’à une echelle inconnue, du bruit ambiant. Cette technique suppose que l’ensemble des donnees est une combinaison lineaire des signaux sources non gaussiens, mais ne requiert pas de connaissance particuliere sur la geometrie de l’ensemble des hydrophones. Un algorithme de detection permettant de separer les vocalisations de baleines franches du bruit ambiant en utilisant un test statistique Kolmogorov-Smirnov est présenté et teste sur des donnees recueillies dans la Baie de Fundy. La performance du detecteur etait telle qu’il a ete possible de réaliser une probabilité de detection d’environ trois quarts, avec une probabilité de fausse alarme d’environ un tiers. L’analyse par composantes independantes n’a donne que des ameliorations mineures compare a l’analyse par composantes principales standard qui a ete utilisee comme etape de pre-traitement. |
| Idioma: | Inglés |
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