TY - GEN
T1 - Passive acoustic detection of modulated underwater sounds from biological and anthropogenic sources
AU - Stolkin, Rustam
AU - Radhakrishnan, Sreeram
AU - Sutin, Alexander
AU - Rountree, Rodney
PY - 2007
Y1 - 2007
N2 - This paper describes an algorithm for the automatic detection of a particular class of underwater sounds, using a single hydrophone. It is observed that many life-forms, systems or mechanisms emit distinctive acoustic signatures which are characterized by packets of relatively high frequency sound that are repeated at regular, low frequency intervals. These types of sounds are commonly produced by biological (e.g. fishes and invertebrates) and anthropogenic (e.g. scuba diver) sources. The algorithm exploits a simple feature, extracted from the raw hydrophone signal, which enables robust detection even in conditions of severe background noise. In order to demonstrate how the algorithm can be used, trial applications are presented for the detection of two different kinds of underwater sound source. First, the algorithm is applied to the problem of detecting soniferous fish sounds, showing that it is possible to robustly automate the detection of instances of cusk-eel presence in hydrophone recordings, thereby simplifying the arduous task of human monitoring of long sound recordings in marine biological research. Second, the algorithm is applied to the problem of automatic diver detection in a noisy urban estuary, demonstrating its potential for harbor security and fleet protection.
AB - This paper describes an algorithm for the automatic detection of a particular class of underwater sounds, using a single hydrophone. It is observed that many life-forms, systems or mechanisms emit distinctive acoustic signatures which are characterized by packets of relatively high frequency sound that are repeated at regular, low frequency intervals. These types of sounds are commonly produced by biological (e.g. fishes and invertebrates) and anthropogenic (e.g. scuba diver) sources. The algorithm exploits a simple feature, extracted from the raw hydrophone signal, which enables robust detection even in conditions of severe background noise. In order to demonstrate how the algorithm can be used, trial applications are presented for the detection of two different kinds of underwater sound source. First, the algorithm is applied to the problem of detecting soniferous fish sounds, showing that it is possible to robustly automate the detection of instances of cusk-eel presence in hydrophone recordings, thereby simplifying the arduous task of human monitoring of long sound recordings in marine biological research. Second, the algorithm is applied to the problem of automatic diver detection in a noisy urban estuary, demonstrating its potential for harbor security and fleet protection.
UR - http://www.scopus.com/inward/record.url?scp=50449103232&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50449103232&partnerID=8YFLogxK
U2 - 10.1109/OCEANS.2007.4449200
DO - 10.1109/OCEANS.2007.4449200
M3 - Conference contribution
AN - SCOPUS:50449103232
SN - 0933957351
SN - 9780933957350
T3 - Oceans Conference Record (IEEE)
BT - Oceans 2007 MTS/IEEE Conference
T2 - Oceans 2007 MTS/IEEE Conference
Y2 - 29 September 2007 through 4 October 2007
ER -