In recent years, sonar systems for surface and underwater vehicles have increased in resolution and become significantly less expensive. As such, these systems are viable at a wide range of price points and are appropriate for a broad set of applications on surface and underwater vehicles. However, to take full advantage of these high-resolution sensors for seafloor mapping tasks an adequate navigation solution is also required. In GPS-denied environments this usually necessitates a simultaneous localization and mapping (SLAM) technique to maintain good accuracy with minimal error accumulation. Acoustic positioning systems such as ultra short baseline (USBL) and long baseline (LBL) are sometimes deployed to provide additional bounds on the navigation solution, but the positional uncertainty of these systems is often much greater than the resolution of modern multibeam or interferometric side scan sonars. As such, subsurface vehicles often lack the means to adequately ground-truth navigation solutions and the resulting bathymetic maps. In this article, we present a dataset with four separate surveys designed to test bathymetric SLAM algorithms using two modern sonars, typical underwater vehicle navigation sensors, and high-precision (2 cm horizontal, 10 cm vertical) real-time kinematic (RTK) GPS ground truth. In addition, these data can be used to refine and improve other aspects of multibeam sonar mapping such as ray-tracing, gridding techniques, and time-varying attitude corrections.
An ocean noise budget is a list of sources of noise along with their average intensity in a particular frequency band [Frisk et al. (2003)]. The budget can be calculated from acoustic data collected by the passive aquatic listener (PAL) systems [Nystuen and Howe (2005); Miller et al. (2008)]. In the far field, the average acoustic intensity of plane waves can be computed in 1/3-octave bands over some duration. The assumption is made that the noise in the band at any one time is dominated by a single, identifiable source such as wind, rain, shipping, fish, marine mammals, etc. The duration and instantaneous intensity of the acoustic signal is used to calculate the average. Identification is carried out using the ratios of various spectral levels as outlined in the work of Ma et al. [(2005)]. We apply the concept of noise budgets to the assessment of the impact of long term noise from offshore wind turbines on marine life. A developer has proposed to construct more than 200 wind turbines south of Rhode Island. A noise budget has been calculated for the region from data collected on PALs. The addition of the 200 turbines will be incorporated into the budget parametrized on source level.
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