Index of content:
Volume 135, Issue 5, May 2014
- ACOUSTIC SIGNAL PROCESSING 
Regularization using Monte Carlo simulation to make optimal beamformers robust to system perturbations135(2014); http://dx.doi.org/10.1121/1.4869676View Description Hide Description
Design of optimal beamformers that withstand system perturbations such as channel mismatch, sensor position error, and pointing error has been a key issue in real-world applications of arrays. This paper aims to characterize the array performance in relation to the random perturbations from a statistical perspective. In the synthesis stage, directivity index and front-to-back ratio are employed as the performance measures for beamformer optimization. Filter coefficients of the arrays are determined using the least-squares and convex optimization approaches using the preceding performance measures. Next, Monte Carlo sampling are conducted to simulate the stochastic system perturbations following either uniform distribution or normal distribution. Statistics including the sample mean, maximum, minimum, and the maximum likelihood (ML) of the preceding performance measures are calculated. Three regularization criteria based on max-mean, max-min, and max-ML of performance measures are proposed for choosing regularization parameters used in beamformer optimization. The max-mean criterion was found most useful to determine either a simple constant or a frequency-dependent regularization parameter. To validate the proposed methods, experiments of beam patterns and automatic speech recognition test were conducted for directional and diffuse noise suppression problems, where optimal beamformers designed with the regularization parameter selected by the preceding procedures were utilized.
Subspace array processing using spatial time-frequency distributions: Applications for denoising structural echoes of elastic targets135(2014); http://dx.doi.org/10.1121/1.4871183View Description Hide Description
Structural echoes of underwater elastic targets, used for detection and classification purposes, can be highly localized in the time-frequency domain and can be aspect-dependent. Hence such structural echoes recorded along a distributed (synthetic) aperture, e.g., using a moving receiver platform, would not meet the stationarity and multiple snapshots requirements of common subspace array processing methods used for denoising array data based on their estimated covariance matrix. To address this issue, this article introduces a subspace array processing method based on the space-time-frequency distribution (STFD) of single-snapshots of non-stationary signals. This STFD is obtained by computing Cohen's class time-frequency distributions between all pairwise combination of the recorded signals along an arbitrary aperture array. This STFD is interpreted as a generalized array covariance matrix which automatically accounts for the inherent coherence across the time-frequency plane of the received nonstationary echoes emanating from the same target. Hence, identifying the signal's subspace from the eigenstructure of this STFD provides a means for denoising these non-stationary structural echoes by spreading the clutter and noise power in the time-frequency domain; as demonstrated here numerically and experimentally using the structural echoes of a thin steel spherical shell measured along a synthetic aperture.
Analysis and measurement of the modulation transfer function of harmonic shear wave induced phase encoding imaging135(2014); http://dx.doi.org/10.1121/1.4869675View Description Hide Description
Shear wave induced phase encoding (SWIPE) imaging generates ultrasound backscatter images of tissue-like elastic materials by using traveling shear waves to encode the lateral position of the scatters in the phase of the received echo. In contrast to conventional ultrasound B-scan imaging, SWIPE offers the potential advantages of image formation without beam focusing or steering from a single transducer element, lateral resolution independent of aperture size, and the potential to achieve relatively high lateral resolution with low frequency ultrasound. Here a Fourier series description of the phase modulated echo signal is developed, demonstrating that echo harmonics at multiples of the shear wave frequency reveal target k-space data at identical multiples of the shear wavenumber. Modulation transfer functions of SWIPE imaging systems are calculated for maximum shear wave acceleration and maximum shear constraints, and compared with a conventionally focused aperture. The relative signal-to-noise ratio of the SWIPE method versus a conventionally focused aperture is found through these calculations. Reconstructions of wire targets in a gelatin phantom using 1 and 3.5 MHz ultrasound and a cylindrical shear wave source are presented, generated from the fundamental and second harmonic of the shear wave modulation frequency, demonstrating weak dependence of lateral resolution with ultrasound frequency.
Green's function retrieval from reflection data, in absence of a receiver at the virtual source position135(2014); http://dx.doi.org/10.1121/1.4869083View Description Hide Description
The methodology of Green's function retrieval by cross-correlation has led to many interesting applications for passive and controlled-source acoustic measurements. In all applications, a virtual source is created at the position of a receiver. Here a method is discussed for Green's function retrieval from controlled-source reflection data, which circumvents the requirement of having an actual receiver at the position of the virtual source. The method requires, apart from the reflection data, an estimate of the direct arrival of the Green's function. A single-sided three-dimensional (3D) Marchenko equation underlies the method. This equation relates the reflection response, measured at one side of the medium, to the scattering coda of a so-called focusing function. By iteratively solving the 3D Marchenko equation, this scattering coda is retrieved from the reflection response. Once the scattering coda has been resolved, the Green's function (including all multiple scattering) can be constructed from the reflection response and the focusing function. The proposed methodology has interesting applications in acoustic imaging, properly accounting for internal multiple scattering.