DocumentCode :
2123139
Title :
An approach to maximum likelihood identification of autoregressive marine mammal sources by passive sonar
Author :
Hernández-Pérez, Eduardo ; Navarro-Mesa, Juan L. ; Míllan-Muñoz, María J.
Author_Institution :
Dept. de Senales y Comunicaciones, ULPGC, Gran Canaria, Spain
Volume :
2
fYear :
2004
fDate :
20-24 Sept. 2004
Firstpage :
1435
Abstract :
This paper proposes a marine mammal classification method that relies in the assumption that the sources are autoregressive (AR). By incorporating the AR coefficients of each source the author make explicit their contribution to the signals at array sensors. A logarithmic likelihood function is introduced in the frequency domain so that all available information from the sources can be incorporated thus letting a proper classification. It is possible to deal with different sources regardless the closeness of their center frequency and their relative location. In the simulations the author explores the potential applications of their method in real situations where it is needed to identify sources as they are detected and localized.
Keywords :
array signal processing; maximum likelihood detection; oceanographic techniques; oceanography; sonar tracking; underwater sound; AR coefficient; autoregressive marine mammal source; frequency domain; logarithmic likelihood function; maximum likelihood identification; passive sonar; potential application; sensor array signal; Frequency; Hidden Markov models; Neural networks; Production; Sea surface; Sensor arrays; Signal generators; Signal processing; Sonar; Whales;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Print_ISBN :
0-7803-8742-2
Type :
conf
DOI :
10.1109/IGARSS.2004.1368689
Filename :
1368689
Link To Document :
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