Detection and classification of North Atlantic right whales in the bay of fundy using independent component analysis
Mots-clés :
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, VocalizationRésumé
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.Fichiers supplémentaires
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