Advanced Methods for Passive Acoustic Detection, Classification, and Localization of Marine Mammals

For effective long-term passive acoustic monitoring of today s large data sets, automated algorithms must provide the ability to detect and classify marine mammal vocalizations and ultimately, in some cases, provide data for estimating the population density of the species present. In recent years,...

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Bibliographische Detailangaben
Hauptverfasser:	Klay, Jonathan, Mellinger, David K, Moretti, David J, Martin, Steve W, Roch, Marie A
Format:	Report
Sprache:	eng
Schlagworte:	ACOUSTIC DETECTION Acoustic Detection and Detectors ALGORITHMS AMPLITUDE API(APPLICATION PROGRAMMING INTERFACES) AQUATIC ANIMALS Biological Oceanography CLASSIFICATION Computer Programming and Software COMPUTER PROGRAMS CROSS CORRELATION CS SVM(CLASS-SPECIFIC SVM) DCL ALGORITHMS DCL SOFTWARE DCL(DETECTION CLASSIFICATION AND LOCALIZATION) DEPTH ECHOLOCATION CLICK CLASSIFICATION MAMMALS MARINE MAMMALS MONITORING MULTI-SENSOR LOCALIZATION Numerical Mathematics PASSIVE ACOUSTIC DETECTION PASSIVE SYSTEMS SVM CLASSIFIERS SVM(SUPPORT VECTOR MACHINE) TONAL SIGNAL DETECTION WHISTLE DETECTION
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Zusammenfassung:	For effective long-term passive acoustic monitoring of today s large data sets, automated algorithms must provide the ability to detect and classify marine mammal vocalizations and ultimately, in some cases, provide data for estimating the population density of the species present. In recent years, researchers have developed a number of algorithms for detecting calls and classifying them to species or species group (such as beaked whales). Algorithms must be robust in real ocean environments where non-Gaussian and non-stationary noise sources, especially vocalizations from similar species, pose significant challenges. In this project, we are developing improved methods for detection, classification, and localization of many types of marine mammal sounds. Additional contract no. N00014-11-IP-20086. Prepared in collaboration with the SPAWAR Systems Center Pacific, San Diego, CA, and the NOAA Pacific Marine Environmental Laboratory (PMEL), Newport, OR. Prepared in cooperation with the Cooperative Institute for Marine Resources Studies, Oregon State University (OSU), Newport, OR, and the Department of Computer Science, San Diego State University (SDSU), San Diego, CA.