Volume 134, Issue 2, August 2013
Index of content:
- UNDERWATER SOUND 
Theory of the directionality and spatial coherence of wind-driven ambient noise in a deep ocean with attenuation134(2013); http://dx.doi.org/10.1121/1.4812270View Description Hide Description
Acoustic attenuation in seawater usually has little effect on the spatial statistics of ambient noise in the ocean. This expectation does not hold, however, at higher frequencies, above 10 kHz, and extreme depths, in excess of 6 km, an operating regime that is within the capabilities of the most recently developed acoustic instrument platforms. To quantify the effects of attenuation, theoretical models for the vertical directionality and the spatial coherence of wind-generated ambient noise are developed in this paper, based on a uniform distribution of surface sources above a semi-infinite, homogeneous ocean. Since there are no bottom reflections, all the noise is downward traveling; and the angular width of the directional density function becomes progressively narrower with increasing frequency because sound from the more distant sources experiences greater attenuation than acoustic arrivals from overhead. This narrowing of the noise lobe modifies the spatial coherence, shifting the zeros in the horizontal (vertical) coherence function to higher (lower) frequencies. In addition, the attenuation modifies the amplitudes of the higher-order oscillations in the horizontal and vertical coherence functions, tending to suppress the former and enhance the latter. These effects are large enough to be detectable with the latest deep-diving sensor technology.
An inter-comparison of sediment classification methods based on multi-beam echo-sounder backscatter and sediment natural radioactivity data134(2013); http://dx.doi.org/10.1121/1.4812858View Description Hide Description
This contribution presents sediment classification results derived from different sources of data collected at the Dordtse Kil river, the Netherlands. The first source is a multi-beam echo-sounder (MBES). The second source is measurements taken with a gamma-ray scintillation detector, i.e., the Multi-Element Detection System for Underwater Sediment Activity (Medusa), towed over the sediments and measuring sediment natural radioactivity. Two analysis methods are employed for sediment classification based on the MBES data. The first is a Bayesian estimation method that uses the average backscatter data per beam and, therefore, is independent of the quality of the MBES calibration. The second is a model-based method that matches the measured backscatter curves to theoretical curves, predicted by a physics-based model. Medusa provides estimates for the concentrations of potassium, uranium, thorium, and cesium, known to be indicative for sediment properties, viz. mean grain size, silt content, and the presence of organic matter. In addition, a hydrophone attached to the Medusa system provides information regarding the sediment roughness. This paper presents an inter-comparison between the sediment classification results using the above-mentioned methods. It is shown that although originating from completely different sources, the MBES and Medusa provide similar information, revealing the same sediment distribution.
134(2013); http://dx.doi.org/10.1121/1.4807819View Description Hide Description
Sequential Bayesian methods such as particle filters have been used to track a moving source in an unknown and space/time-evolving ocean environment. These methods treat both the source and the ocean parameters as non-stationary unknown random variables and track them via the multivariate posterior probability density function. Particle filters are numerical methods that can operate on nonlinear systems with non-Gaussian probability density functions. Particle smoothers are a natural extension to these filters. A smoother is appropriate in applications where data before and after the time of interest are readily available. Both past and “future” measurements are exploited in smoothers, whereas filters just use past measurements. Geoacoustic and source tracking is performed here using two smoother algorithms, the forward-backward smoother and the two-filter smoother. Smoothing is demonstrated on experimental data from both the SWellEx-96 and SW06 experiments where the parameter uncertainty is reduced relative to just filtering alone.