The wavenumber algorithm for full-matrix imaging using an ultrasonic array

Ultrasonic imaging using full-matrix capture, e.g., via the total focusing method (TFM), has been shown to increase angular inspection coverage and improve sensitivity to small defects in nondestructive evaluation. In this paper, we develop a Fourier-domain approach to full-matrix imaging based on t...

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Bibliographic Details
Published in:IEEE transactions on ultrasonics, ferroelectrics, and frequency control ferroelectrics, and frequency control, 2008-11, Vol.55 (11), p.2450-2462
Main Authors: Hunter, A.J., Drinkwater, B.W., Wilcox, P.D.
Format: Article
Language:English
Subjects:
Acoustic signal processing
Acoustics
Algorithms
Array signal processing
Arrays
Exact sciences and technology
Focusing
Fundamental areas of phenomenology (including applications)
Geometry
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Imaging
Inspection
Inverse problems
Mathematical model
Mathematical models
Physics
Propagation delay
Reproducibility of Results
Sensitivity and Specificity
Studies
Synthetic aperture sonar
Time domain analysis
Transducers
Ultrasonic imaging
Ultrasonic testing
Ultrasonography - instrumentation
Ultrasonography - methods
Wavenumber
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Summary:Ultrasonic imaging using full-matrix capture, e.g., via the total focusing method (TFM), has been shown to increase angular inspection coverage and improve sensitivity to small defects in nondestructive evaluation. In this paper, we develop a Fourier-domain approach to full-matrix imaging based on the wavenumber algorithm used in synthetic aperture radar and sonar. The extension to the wavenumber algorithm for full-matrix data is described and the performance of the new algorithm compared with the TFM, which we use as a representative benchmark for the time-domain algorithms. The wavenumber algorithm provides a mathematically rigorous solution to the inverse problem for the assumed forward wave propagation model, whereas the TFM employs heuristic delay-and-sum beamforming. Consequently, the wavenumber algorithm has an improved point-spread function and provides better imagery. However, the major advantage of the wavenumber algorithm is its superior computational performance. For large arrays and images, the wavenumber algorithm is several orders of magnitude faster than the TFM. On the other hand, the key advantage of the TFM is its flexibility. The wavenumber algorithm requires a regularly sampled linear array, while the TFM can handle arbitrary imaging geometries. The TFM and the wavenumber algorithm are compared using simulated and experimental data.
ISSN:0885-3010
1525-8955
DOI:10.1109/TUFFC.952