Development of a shallow water ambient noise database

Abstract

Abstract-The number of underwater activities and experiments in tropical waters has been growing; people are increasingly becoming interested in the development of underwater applications that rely on acoustic communications. Ambient noise is a limiting factor in the performance of underwater acoustic detection and communication systems at shallow water. Knowledge of ambient noise characteristics at a location will be helpful for ambient noise imaging systems like ROMANIS, built at Acoustic Research Laboratory.The Singapore straits and surrounding waters contain some of the busiest shipping channels in the world. Monitoring of ambient noise is of crucial interest to acousticians and oceanographers due to the high level of shipping and snapping shrimp noise in the region. Since there was no such systematic ambient noise database existing to support oceanographers and acousticians, the Acoustic Research Laboratory (ARL) at the Tropical Marine Science Institute (TMSI) has embarked on developing a shallow water ambient noise database. This Graphical User Interface (GUI) -based database will benefit and enhance the research and development of marine acoustic systems. This paper describes the collection of ambient noise data and the structured compilation of this information into a useful database. The data collected covers a frequency range of 11 -8300 Hz. The data is indexed and stored in a database and presented to the user via a GUI. The GUI uses an approach similar to typical Geographical Information System (GIS) databases. The user is able to select different layers of information on a map. The user may search for ambient noise data based on various parameters such as location of data collections or classification of the environment. The GUI is also integrated with Matlab ® , popular mathematical analysis software, to display the time series, power spectral density and 1/3 rd octave spectrogram of the ambient noise data.The database GUI, some example data and a summary of the collected ambient noise data will be presented. The high levels of noise due to shipping and snapping shrimp are all readily apparent in the data; with typical intensity levels considerably exceeding classic reported values. Shipping noise is reported to dominate the frequency range below 1 kHz. Snapping shrimp noise is found in all warm and shallow waters. The ambient noise data collected from near a fish farm area shows that the snapping shrimp noise is dominant above 2kHz.

ON CLICKING SOUNDS IN UK WATER & A PRELIMINARY STUDY OF THEIR POSSIBLE BIOLOGICAL ORIGIN

“…The solutions to (2) are obtained using a NelderMeade optimisation routine [18]. This routine is started using 100 random initialisations; the random starting conditions are generated using uniform random numbers generated over the region [5,5] independently for each of the 3 coordinates. The final solution is obtained by selecting the solution which has the smallest cost function value from the 100 realisations.…”

“…[3] reported that specimens of snapping shrimp collected in the Bahamas kept in glass aquaria survived well as long as the water temperature remained between 14 o C and 24 o C. However, they also reported that the 11 o C winter seasurface isothermal line seemed to mark the approximate northern and southern limits of the range in which snapping shrimp live. Johnson et al [4] point out that the 11 o C isothermal line of the time passed some 7 o latitude (almost 800 km) South of southernmost England [5]. However there is some historical evidence of snapping shrimp in UK waters.…”

A GTCC-Based Underwater HMM Target Classifier with Fading Channel Compensation

“…The paper also reviews the major problems in noise measurement, noise reduction, and its prevention. Pieng et al [8] highlight the collection of ambient noise data and the structured compilation of the collected information into a useful database. Kamal et al [9] present an attempt to lift the latent underwater source signals from the observed noise mixture utilizing independent component analysis (ICA).…”