Volume 113, Issue 5, May 2003
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
113(2003); http://dx.doi.org/10.1121/1.1554691View Description Hide Description
The performance bounds of a passive acoustic array operating in a turbulent medium with fluctuations described by a von Kármán spectrum are investigated. This treatment considers a single, monochromatic, plane-wave source at near-normal incidence. A line-of-sight propagation path is assumed. The primary interests are in calculating the Cramer–Rao lower bounds of the azimuthal and elevational angles of arrival and in observing how these bounds change with the introduction of additional unknowns, such as the propagation distance, turbulence parameters, and signal-to-noise ratio. In both two and three dimensions, it is found that for large values of the index-of-refraction variance, the Cramer–Rao lower bounds of the angles of arrival increase significantly at large values of the normalized propagation distance. For small values of the index-of-refraction variance and normalized propagation distance, the signal-to-noise ratio is found to be the limiting factor. In the two-dimensional treatment, it is found that the estimate of the angle of arrival will decouple from the estimates of the other parameters with the appropriate choice of array geometry. In three dimensions, again with an appropriate choice of array geometry, the estimates of the azimuth and elevation will decouple from the estimates of the other parameters, but due to the constraints of the model, will remain coupled to one another.
113(2003); http://dx.doi.org/10.1121/1.1561817View Description Hide Description
Application of adaptive matched field processing to the problem of detecting quiet targets in shallow water is complicated by source motion, both the motion of the target and the motion of discrete interferers. Target motion causes spreading of the target peak, thereby reducing output signal power. Interferer motion increases the dimensionality of the interference subspace, reducing adaptive interference suppression. This paper presents three techniques that mitigate source motion problems in adaptive matched field processing. The first involves rank reduction, which enables adaptive weight computation over short observation intervals where motion effects are less pronounced. The other two techniques specifically compensate for source motion. Explicit target motion compensation reduces target motion mismatch by focusing snapshots according to a target velocity hypothesis. And time-varying interference filtering places time-varying nulls on moving interferers not otherwise suppressed by adaptive weights. The three techniques are applied to volumetric array data from the Santa Barbara Channel Experiment and are shown to improve output signal-to-background-plus-noise ratio by more than 3 dB over the standard minimum-variance, distortionless response adaptive beam-former. Application of the techniques in some cases proves to be the difference between detecting and not detecting the target.
113(2003); http://dx.doi.org/10.1121/1.1566976View Description Hide Description
Optimal detection of a striplike crack residing in an isotropic elastic solid with coarse microstructure by means of ultrasonicnondestructive evaluation(NDE) is considered. A physics-based approach to derive an optimal detector, which achieves the theoretical limitations constrained by the underlying physics, is presented. State-of-the-art physical models of crack echoes and of stochastic backscattering from the material structure in elastic solids are introduced and unified with the theory of optimal detection to yield a practically useful nonlinear filter bank implementation of the optimal detector.Monte Carlo simulations of the detection performance for the special case of a striplike crack with uncertain angular orientation are presented in the form of receiver operating characteristics (ROCs). These new results represent the physical limitations for detecting a crack under the stated conditions and serve as performance bounds to which other detectors should be compared. A physics-based generalized likelihood ratio (GLR) detector, which relies on the same nonlinear filter bank as the optimal detector, is also presented for the special case of a striplike crack. A comparison between the optimal and the GLR detectors shows that the GLR detector only slightly reduces the performance.
113(2003); http://dx.doi.org/10.1121/1.1566975View Description Hide Description
The theory of time-reversal super-resolution imaging of point targets embedded in a reciprocal background medium [A. J. Devaney, “Super-resolution imaging using time-reversal and MUSIC,” J. Acoust. Soc. Am. (to be published)] is generalized to the case where the transmitter and receiver sensor arrays need not be coincident and for cases where the background medium can be nonreciprocal. The new theory developed herein is based on the singular value decomposition of the generalized multistatic data matrix of the sensor system rather than the standard eigenvector/eigenvalue decomposition of the time-reversal matrix as was employed in the above-mentioned work and other treatments of time-reversal imaging [Prada, Thomas, and Fink, “The iterative time reversal process: Analysis of the convergence,” J. Acoust. Soc. Am. 97, 62 (1995); Prada et al., “Decomposition of the time reversal operator: Detection and selective focusing on two scatterers,” J. Acoust. Soc. Am. 99, 2067 (1996)]. A generalized multiple signal classification (MUSIC) algorithm is derived that allows super-resolution imaging of both well-resolved and non-well-resolved point targets from arbitrary sensor array geometries. MUSIC exploits the orthogonal nature of the scatterer and noise subspaces defined by the singular vectors of the multistatic data matrix to form scatterer images. The time-reversal/MUSIC algorithm is tested and validated in two computer simulations of offset vertical seismic profiling where the sensorsources are aligned along the earth’s surface and the receiver array is aligned along a subsurface borehole. All results demonstrate the high contrast, high resolution imaging capabilities of this new algorithm combination when compared with “classical” backpropagation or field focusing. Above and beyond the application of seismo-acousticimaging, the time-reversal super-resolution theory has applications in ocean acoustics for target location, and ultrasonic nondestructive evaluation of parts.
113(2003); http://dx.doi.org/10.1121/1.1561498View Description Hide Description
In this paper we propose and demonstrate a method to obtain simultaneous dual source–receiver impulse responses in acoustical systems using binary maximum-length sequences (MLS). A binary MLS and its reversed-order sequence form a reciprocal MLS pair. Their correlation property includes a two-valued “pulse-like” autocorrelation function and a relatively smaller-valued cross-correlation function. This unique property, along with other number-theory properties, makes the reciprocal MLS pair suitable for simultaneous dual source cross-correlation measurements. In the measurement of a dual source system, each of the reciprocal MLS pairs simultaneously excite one of two separate sources, one or several receiver signals cross-correlate in turn with each of the MLS pairs, resulting in impulse responses associated with two separate sources. The proposed method is particularly valuable for system identification tasks with multiple sound/vibration sources and receivers that have to be accomplished in a limited time period. A fast algorithm called a fast MLS transform is exploited for the cross-correlation. In this paper we propose a fast MLS transform pair for the reciprocal MLS pairs. Its efficiency lies in the requirement of one single permutation matrix for a pair of two fast MLS transforms. Its feasibility and usefulness in the acoustical measurements are demonstrated using experimental results.