Subsampling Approaches for Compressed Sensing with Ultrasound Arrays in Non-Destructive Testing
1
Fraunhofer IZFP, 66123 Saarbrücken, Germany
2
Electronic Measurements and Signal Processing, TU Ilmenau, 98693 Ilmenau, Germany
3
AutomaTiQ, htw saar, 66117 Saarbrücken, Germany
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(23), 6734; https://doi.org/10.3390/s20236734
Received: 2 November 2020
/
Revised: 20 November 2020
/
Accepted: 23 November 2020
/
Published: 25 November 2020
(This article belongs to the Special Issue Phased Array Ultrasonic Transducers (PAUT) and Techniques for Nondestructive Inspection of Structures and Materials)
Full Matrix Capture is a multi-channel data acquisition method which enables flexible, high resolution imaging using ultrasound arrays. However, the measurement time and data volume are increased considerably. Both of these costs can be circumvented via compressed sensing, which exploits prior knowledge of the underlying model and its sparsity to reduce the amount of data needed to produce a high resolution image. In order to design compression matrices that are physically realizable without sophisticated hardware constraints, structured subsampling patterns are designed and evaluated in this work. The design is based on the analysis of the Cramér–Rao Bound of a single scatterer in a homogeneous, isotropic medium. A numerical comparison of the point spread functions obtained with different compression matrices and the Fast Iterative Shrinkage/Thresholding Algorithm shows that the best performance is achieved when each transmit event can use a different subset of receiving elements and each receiving element uses a different section of the echo signal spectrum. Such a design has the advantage of outperforming other structured patterns to the extent that suboptimal selection matrices provide a good performance and can be efficiently computed with greedy approaches.
View Full-Text
Keywords:
Full Matrix Capture; compressed sensing; sparse array
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
MDPI and ACS Style
Pérez, E.; Kirchhof, J.; Krieg, F.; Römer, F. Subsampling Approaches for Compressed Sensing with Ultrasound Arrays in Non-Destructive Testing. Sensors 2020, 20, 6734. https://doi.org/10.3390/s20236734
AMA Style
Pérez E, Kirchhof J, Krieg F, Römer F. Subsampling Approaches for Compressed Sensing with Ultrasound Arrays in Non-Destructive Testing. Sensors. 2020; 20(23):6734. https://doi.org/10.3390/s20236734
Chicago/Turabian StylePérez, Eduardo, Jan Kirchhof, Fabian Krieg, and Florian Römer. 2020. "Subsampling Approaches for Compressed Sensing with Ultrasound Arrays in Non-Destructive Testing" Sensors 20, no. 23: 6734. https://doi.org/10.3390/s20236734
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
