Detection and localization of Goliath grouper using their low-frequency pulse sounds

Area of Science:

• Marine Biology
• Acoustics
• Signal Processing

Background:

• Underwater acoustic monitoring is crucial for marine organism tracking.
• Existing methods often struggle with large datasets and precise localization of low-frequency sounds.

Purpose of the Study:

• To develop and deploy an automated model for detecting and localizing marine organisms using their low-frequency pulse sounds.
• To improve the accuracy and efficiency of underwater acoustic data analysis.

Main Methods:

• A two-stage approach was implemented: sound detection and localization.
• An adaptive matched filter (MF) was used for pulse detection and timing.
• Time difference of arrival (TDOA) algorithm was employed for source localization.

Main Results:

• The model achieved source location accuracy within the array dimensions.
• Localization error was approximately 2 meters for a 50-meter hydrophone array.
• The method successfully localized Goliath grouper calls.

Conclusions:

• The developed automated system offers precise small-scale movement tracking for sound-producing marine organisms.
• This method enables efficient processing of extensive acoustic data for ecological studies.