Volume 106, Issue 4, October 1999
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
106(1999); http://dx.doi.org/10.1121/1.427933View Description Hide Description
This paper presents a new sonar target classification approach based on the use of time-frequency filters. Their design is carried out from the free field response of a reference target, and more precisely from the analysis of echo formation mechanisms in the time-frequency plane. The study of the relevance and the robustness of this approach in approximately real sonar conditions is conducted from experimental measurements in a tank. A data base is set up that contains a large set of target responses in the free field, near different interfaces and in waveguide situations. First, the efficiency of the method for the recognition of a nickelmolybdenum spherical shell, corresponding to a class of man made targets whose size is much smaller than the sonar beam (finite size) is shown (100% of recognition). Second, a classification procedure between different targets of finite size is conducted: more than 85% of good classification is obtained (except for the marble solid target). Finally, in the presence of numerical noise, the method is found to be robust even for a low signal to noise ratio.
106(1999); http://dx.doi.org/10.1121/1.427934View Description Hide Description
This paper presents a statistical freeze bath method for geoacoustic inversion that emphasizes the search for a distribution of models that fit the data well. Contrary to simulated annealing optimization, the freeze bath samples the multidimensional model parameter space at constant freeze probability, corresponding to fixed temperatures for each parameter. The sampling process uses a heat bath algorithm as a Boltzmann sampling tool to carry out a global search over the model parameter space. The conventional heat bath algorithm is modified to sample on a fuzzy grid in order to access the entire range of parameter values. The inversion provides a set of good models that indicates how well the model parameters are constrained by the data, and reveals the degree of correlation between parameters. The efficiency of the search process is improved by reparameterizing the original model parameters to a new set based on the eigenvectors of the model covariance matrix. The inversion performance of the freeze bath is demonstrated using simulated data for a simple geoacoustic model. The method is applied to shallow water broadband data obtained during the Haro Strait geoacoustic tomography experiment to estimate a geoacoustic profile at the site.