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

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2012
Accession Number
ADA573543

Entities

People

  • David J. Moretti
  • David K. Mellinger
  • Jonathan Klay
  • Marie A. Roch
  • Steve W Martin

Organizations

  • National Oceanic and Atmospheric Administration

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acoustic Detection
  • Acoustic Detectors
  • Algorithms
  • Animals
  • Classification
  • Computer Vision
  • Cross Correlation
  • Data Sets
  • Detection
  • Detectors
  • Hidden Markov Models
  • Machine Learning
  • Mammals
  • Marine Mammals
  • Odontocetes
  • Supervised Machine Learning
  • Whales

Fields of Study

  • Environmental science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Marine Mammal Biology
  • Systems Analysis and Design