Direct under-sampling compressive sensing method for underwater echo signals and physical implementation

5Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

Compressive sensing can guarantee the recovery accuracy of suitably constrained signals by using sampling rates much lower than the Nyquist limit. This is a leap from signal sampling to information sampling. The measurement matrix is key to implementation but limited in the acquisition systems. This article presents the critical elements of the direct under-sampling-compressive sensing (DUS-CS) method, constructing the under-sampling measurement matrix, combined with a priori information sparse representation and reconstruction, and we show how it can be physically implemented using dedicated hardware. To go beyond the Nyquist constraints, we show how to design and adjust the sampling time of the A/D circuit and how to achieve low-speed random non-uniform direct under-sampling. We applied our method to data measured with different compression ratios (volume ratios of collected data to original data). It is shown that DUS-CS works well when the SNR is 3 dB, 0 dB,-3 dB, and-5 dB and the compression ratio is 50%, 20%, and 10%, and this is validated with both simulation and actual measurements. The method we propose provides an effective way for compressed sensing theory to move toward practical field applications that use underwater echo signals.

Cite

CITATION STYLE

APA

Sun, T., Li, J., & Blondel, P. (2019). Direct under-sampling compressive sensing method for underwater echo signals and physical implementation. Applied Sciences (Switzerland), 9(21). https://doi.org/10.3390/app9214596

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free