Volume 119, Issue 3, March 2006
Index of content:
- UNDERWATER SOUND 
119(2006); http://dx.doi.org/10.1121/1.2161439View Description Hide Description
Directional broadband reverberation can be exploited for rapidly probing seabed variability over large areas O ; the data need not be calibrated. Seabed variability thus mapped inherently combines spatial variability in geoacoustic properties that control reflection and those that control scattering. It is shown that in some cases, the variability can be separated. The method is applied to measurements in the Straits of Sicily where the data indicate the existence of two provinces where the statistics of the geoparameters are distinct. Three attributes of each province are quantified: the province boundaries, measures of spatial variability and/or uncertainty, and the location of discrete scattering features (that may lead to sonar clutter). One province is quite large and exhibits remarkably little spatial variability. The variability is probed on lateral scales , yet the ratio of the seabed geoparameters varies less than 3 dB from over . While this result seems contrary to prevailing notions of extreme seabed variability in shallow water, it indicates that certain kinds of geophysical (and concomitant geoacoustic) variability may be averaged in such a way that the seabed appears approximately homogeneous to long-range acoustic systems.
119(2006); http://dx.doi.org/10.1121/1.2161430View Description Hide Description
This paper presents results which relate to the geometry of various examined Haro Strait scenarios. In particular, for each data scenario the source range, source depth, individual phone ranges, individual phone depths, and an average water depth may be determined based on the time domain signals alone. The time differences for each phone for (1) surface reflected minus direct arrivals, and (2) bottom reflected minus direct arrivals are used to estimate potential positions from elementary geometric considerations [similar to Michalopoulou, and Ma (unpublished)]. Nonuniqueness is still a nasty issue and is examined here. However, additional constraints on each scenario to guarantee realism, e.g., the array must be quasivertical with phones apart with no extreme snaking of the array, sources can only be within certain ranges and depths, the top array phone depth and average water depths can only be within certain regimes, etc., eliminate many false solutions. Finally and convincingly, some of the optimal positions are “confirmed” by simulating the signals for the predicted geometries by means of a pulse PE (ramgeo) propagation code (courtesy of M. Collins) and then comparing those simulated signals with the observed data. Once the scenario geometry has been estimated, proper geoacoustic inversion for bottom properties can proceed via the SUB-RIGS method [Tolstoy, IEEE J. Ocean. Eng.29, 59–77 (Year: 2004(b))]. These subsequent inversions will be discussed in a follow-up paper.
Classification of shallow-water acoustic signals via alpha-Stable modeling of the one-dimensional wavelet coefficients119(2006); http://dx.doi.org/10.1121/1.2165003View Description Hide Description
A novel statistical scheme is presented for the classification of shallow water acoustic signals according to the environmental parameters of the medium through which they have propagated. An efficient way to classify these signals is important for inverse procedures in underwater acoustics aiming at the recovery of the geoacoustic parameters of an oceanic environment, using measurements of the acoustic field due to an acoustic source. An important issue in this procedure is the determination of an efficient “observable” of the acoustic signal (feature extraction), which characterizes the signal in connection with the recoverable parameters. The proposed method is based on a transformation of the acoustic signals via a one-dimensional (1D) wavelet decomposition and then by fitting the distribution of the subband coefficients using an appropriate function. We observe that statistical distributions with heavy algebraic tails, such as the alpha-Stable family, are often very accurate in capturing the non-Gaussian behavior of the subband coefficients. As a result, the feature extraction step consists of estimating the parameters of the alpha-Stable model, while the similarity between two distinct signals is measured by employing the Kullback–Leibler Divergence between their corresponding alpha-Stable distributions. The performance of the proposed classification method is studied using simulated acoustic signals generated in a shallow water environment.
119(2006); http://dx.doi.org/10.1121/1.2167058View Description Hide Description
In this paper, long-range propagation of low-frequency sound through an ocean waveguide with random inhomogeneities in the sound speed is studied. Closed equations for the mean field and correlation function of the sound field are derived using the Chernov method. These equations can be considered as a generalization of equations derived by Dozier and Tappert [J. Acoust. Soc. Am.63, 353–365 (1978)], which accounts for 3D effects and cross-modal correlations. The equations derived in this paper in a general form are similar to the equations obtained by many other authors. However, without simplifications these equations are difficult to solve even numerically due to high dimension of the matrices appearing in the equations. Some simplifications of the equations for the mean field and correlation function are suggested that account for narrowness of the angular spectrum of the scattered acoustic field and which make these equations amenable for numerical implementation. To study solutions of the simplified equations, they are additionally averaged along the sound propagation path. This allows us to obtain some analytical results. Using the theory developed, the horizontal coherence length of the sound field is estimated for the GM spectrum of internal waves.
119(2006); http://dx.doi.org/10.1121/1.2165070View Description Hide Description
Despite the advantages clearly demonstrated by ocean acoustic tomography (OAT) when compared to other ocean monitoring techniques, it suffers from several technical-related drawbacks. One is the requirement for rather expensive equipment to be maintained and operated at several locations in order to obtain sufficient source–receiver propagation paths to cover a given ocean volume. This paper presents the preliminary feasibility tests of a concept that uses ships of opportunity as sound sources for OAT. The approach adopted in this paper views the tomographic problem as a global inversion that includes determining both the emitted signal and the environmental parameters, which is a similar problem to that seen in blind channel identification and was therefore termed blind ocean acoustic tomography(BOAT).BOAT was tested on a data set acquired in October 2000 in a shallow-water area off the west coast of Portugal, including both active and passive (shipnoise) data. Successful results show that BOAT is able to estimate detailed water column temperature profiles coherent with independent measurements in intervals where the uncontrolled source signal (shipnoise) presents a sufficient bandwidth and signal-to-noise ratio, which clearly define the limitations of the presented method.