Publications by authors named "Dag Tollefsen"

This paper presents analysis of a 1-year (2018-2019) recording of ambient noise (40-2000 Hz) at a seasonally ice-covered location on the continental slope between the Svalbard archipelago and the Nansen Basin, northeast Atlantic Arctic. Time series of ambient noise show highest correlations with ice concentration and wind speed. A log-wind speed regression model is fitted to spectral noise data for three categories of ice concentration.

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This paper presents data from mid-frequency (4-8 kHz) under-ice acoustic transmission and communication experiments in the Nansen Basin and in the Beaufort Sea of the Arctic Ocean. Measured impulse responses to range ∼10 km showed considerable delay spread between distinct groups of arrivals due to surface-ducted and bottom-reflected paths. The relative strengths of these groups depend on duct and under-ice properties.

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This paper applies a non-linear Bayesian marginalization approach to ship spectral source level estimation in shallow water with unknown seabed properties and uncertain source depth. The algorithm integrates the posterior probability density over seabed models sampled via trans-dimensional Bayesian matched-field inversion and over depths/ranges of multiple point sources (representing different noise-generating components of a large ship) via Metropolis-Hastings sampling. Source levels and uncertainty are derived from marginal distributions for source strength.

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This paper considers concurrent matched-field processing of data from multiple, spatially-separated acoustic arrays with application to towed-source data received on two bottom-moored horizontal line arrays from the SWellEx-96 shallow water experiment. Matched-field processors are derived for multiple arrays and multiple-snapshot data using maximum-likelihood estimates for unknown complex-valued source strengths and unknown error variances. Starting from a coherent processor where phase and amplitude is known between all arrays, likelihood expressions are derived for various assumptions on relative source spectral information (amplitude and phase at different frequencies) between arrays and from snapshot to snapshot.

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A sonobuoy field was deployed in the Marginal Ice Zone of the Fram Strait in June 2011 to study the spatial variability of ambient noise. High noise levels observed at 10-200 Hz are attributed to distant (1400 km range) seismic exploration. The noise levels decreased with range into the ice cover; the reduction is fitted by a spreading loss model with a frequency-dependent attenuation factor less than for under-ice interior Arctic propagation.

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This letter develops a Bayesian focalization approach for three-dimensional localization of an unknown number of sources in shallow water with uncertain environmental properties. The algorithm minimizes the Bayesian information criterion using adaptive hybrid optimization for environmental parameters, Metropolis sampling for source bearing, and Gibbs sampling for source ranges and depths. Maximum-likelihood expressions are used for unknown complex source strengths and noise variance, which allows these parameters to be sampled implicitly.

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This paper develops a non-linear Bayesian marginalization approach for three-dimensional source tracking in shallow water with uncertain environmental properties. The algorithm integrates the posterior probability density via a combination of Metropolis-Hastings sampling over environmental and bearing model parameters and Gibbs sampling over source range/depth, with track constraints on source velocity applied. Marginal distributions for source range/depth and source bearing are derived, with source position uncertainties estimated from the distributions.

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This paper develops an approach to three-dimensional source tracking in an uncertain ocean environment using a horizontal line array (HLA). The tracking algorithm combines matched-field focalization for environmental (seabed and water column) and source-bearing model parameters with the Viterbi algorithm for range-depth estimation and includes physical constraints on source velocity. The ability to track a source despite environmental uncertainty is examined using synthetic test cases for various track geometries and with varying degrees of prior information for environmental parameters.

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This paper applies geoacoustic inversion to low-frequency narrow-band acoustic data from a quiet surface ship recorded on a bottom-moored horizontal line array in shallow water. A Bayesian matched-field inversion method is employed which quantifies geoacoustic uncertainties and allows for meaningful comparison of inversion results from different data sets. Geoacoustic inversion results for ship-noise data are compared with inversion results for multitone data from a towed controlled source collected in the same experiment, and with independent geophysical measurements.

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