Ambient noise source characterization using spectral, coherence, and directionality estimates at Kongsfjorden.

Ambient noise measurements from an Arctic fjord during summer and winter are analyzed using spectral, coherence, and directionality estimates from a vertically separated pair of hydrophones. The primary noise sources attributed to wind, shipping, and ice activity are categorized and coherence is arrived at. Estimates of the noise field directionality in the vertical and its variation over time and between seasons are used to strengthen the analysis of the time-varying nature of noise sources.

Anthropogenic sound field and noise mapping in an Arctic fjord during summer.

Sound Pressure Levels were recorded using an Automated Noise Measurement System, during July 2015 - April 2016 at the Kongsfjorden, Arctic. The fjord houses the NyAlesund port and has many vessels plying during summer, which contributes to anthropogenic noise. Spectral distribution and average sound level at 1/3-octave band from 63 Hz to 5000 Hz has been analyzed and correlated with Automatic Identification System marine traffic data.

Geoacoustic inversion in shallow tropical waters for a silty and sandy seabed.

Seabed parameters are inverted from ambient noise measurements at two shallow tropical environments with dissimilar seabed characteristics, a silty and a sandy seabed, using an approach that matches the measured and modeled complex vertical coherence. Coherence is modeled using the Green's function output from the model oases, along with theoretical formulation, for a range independent environment. Genetic algorithm is used to search the model parameter space consisting of sound speed, density, and attenuation in the sediment layers and half-space.

Seabed characteristics from ambient noise at three shallow water sites in Northern Indian Ocean.

Ambient noise measurements at three sites along the Indian continental shelf, with different water column and seabed, are analyzed to derive vertical directionality and further estimation of seabed characteristics. Directionality pattern is interpreted using features in the sound speed profiles, in terms of noise notch, surface duct, surface bottom reflections, direct arrivals, and high bottom loss arrivals. Reflection loss estimated from the field directionality is seen to be the same for a particular site and gives an estimate of the sea bottom.