Volume 115, Issue 1, January 2004
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
115(2004); http://dx.doi.org/10.1121/1.1635407View Description Hide Description
This study describes a method for determining the statistical confidence in estimates of direction-of-arrival and trace velocity stemming from signals present in atmospheric infrasound data. It is assumed that the signal source is far enough removed from the infrasound sensor array that a plane-wave approximation holds, and that multipath and multiple source effects are not present. Propagation path and medium inhomogeneities are assumed not to be known at the time of signal detection, but the ensemble of time delays of signal arrivals between array sensor pairs is estimable and corrupted by uncorrelated Gaussian noise. The method results in a set of practical uncertainties that lend themselves to a geometric interpretation. Although quite general, this method is intended for use by analysts interpreting data from atmospheric acoustic arrays, or those interested in designing and deploying them. The method is applied to infrasound arrays typical of those deployed as a part of the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty Organization.
115(2004); http://dx.doi.org/10.1121/1.1632482View Description Hide Description
Time-reversal is addressed for imaging elastic targets situated in an acoustic waveguide. It is assumed that the target-sensor range is large relative to the channel depth. We investigate the theory of wideband time-reversal imaging of an extended elastic target, for which the target dimensions are large relative to the principal wavelengths. When performing time-reversal imaging one requires a forward model for propagation through the channel, and the quality of the resulting image may be used as a measure of the match between the modeled and actual (measured) channel parameters. It is demonstrated that the channel parameters associated with a given measurement may be determined via a genetic-algorithm (GA) search in parameter space, employing a cost function based on the time-reversal image quality. Example GA channel-parameter-inversion results and imagery are presented for measured at-sea data.
115(2004); http://dx.doi.org/10.1121/1.1625683View Description Hide Description
The problem of inferring unknown geometry and material parameters of a waveguidemodel from noisy samples of the associated modal dispersion curves is considered. In a significant reduction of the complexity of a common inversion methodology, the inner of two nested iterations is eliminated: The approach described does not employ explicit fitting of the data to computed dispersion curves. Instead, the unknown parameters are adjusted to minimize a cost function derived directly from the determinant of the boundary condition system matrix. This results in an efficient inversion scheme that, in the case of noise-free data, yields exact results. Multimode data can be simultaneously processed without extra complications. Furthermore, the inversion scheme can accommodate an arbitrary number of unknown parameters, provided that the data have sufficient sensitivity to these parameters. As an important application, we consider the sonic guidance condition for a fluid-filled borehole in an elastic, homogeneous, and isotropic rock formation for numerical forward and inverse dispersion analysis. We investigate numerically the parametric inversion with errors in the model parameters and the influence of bandwidth and noise, and examine the cases of multifrequency and multimode data, using simulated flexural and Stoneley dispersion data.