Index of content:
Volume 118, Issue 4, October 2005
- UNDERWATER SOUND 
118(2005); http://dx.doi.org/10.1121/1.2035590View Description Hide Description
Examples of the sonic-boom generated sound field under a wavy air–water interface based on the theory of Cheng and Lee [J. Fluid Mech.514, 281–312 (2004)] are studied to determine the surface-wave influence on sound-pressure level, frequency range, and waveform characteristics of disturbances generated by an aerial sonic-boom wave over water. The study substantiates that, owing to their much lower attenuation rate, the time-dependent disturbances produced by the interaction with a surface-wave train can be comparable to, and overwhelm the flat-ocean (Sawyers) wave field at large as well as moderate depth levels, depending on Mach number, surface-wave length and-height, and the alignment angle of surface waves with respect to the flight track. Computed examples, assuming a signature length and a peak sea-level overpressure, show that, under a mildly wavy ocean, sonic-boom disturbances at sound-pressure level of (re: ) can reach a depth of , where the dominant waveform evolves into an infrasound wave packet of frequency .
118(2005); http://dx.doi.org/10.1121/1.2011410View Description Hide Description
Tracking of individual fish targets using a split-beam echosounder is a common method for investigating fish behavior. When mounted on a floating platform like a ship or a buoy, the transducer movement often complicates the process. This paper presents a framework for tracking single targets from such a platform. A filter based on the correlated fish movements between pings is developed to estimate the platform movement, and an extended Kalman filter is used to combine the split-beam measurements and the platform-position estimates. Different methods for gating and data association are implemented and tested with respect to data-association errors, using manually tracked data from a free-floating buoy as a reference. The data association was improved by utilizing the estimated velocity for each track to predict the location of the next observation. The data association was more robust when estimates of platform tilt/roll were used. Other techniques to estimate position and velocity, like linear regression and smoothing splines, were implemented and tested on a simulated data set. The platform-state estimation improved the estimates for methods like the Kalman filter and a smoothing spline with cross validation, but not for robust methods like linear regression and smoothing spline with a fixed degree of smoothing.
118(2005); http://dx.doi.org/10.1121/1.2010309View Description Hide Description
In theory, matched field processing offers the significant benefit of higher signal gains and increased localization capability. However, this has not been robustly observed in practice because of inherent uncertainties about details of the shallow water propagation environments which limit the prediction of the channel response. The use of guide sources to directly measure the transfer function between source and receiver arrays has been proposed as a means for reducing mismatch. However, the guide source measurement only provides a measured transfer function at the guide source location. In this paper a method of depth-shifting guide source observations is proposed, making it possible to estimate transfer functions for points in the ocean other than the guide source location. The proposed depth-shifting process does not require knowledge of environmental parameters. The theoretical background for the technique is developed below and its range of applicability is examined