• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Adaptive Selective Compressive Sensing based Signal Acquisition Oriented toward Strong Signal Noise Scene

Vol. 9, No. 9, September 29, 2015
10.3837/tiis.2015.09.015, Download Paper (Free):

Abstract

This paper addresses the problem of signal acquisition with a sparse representation in a given orthonormal basis using fewer noisy measurements. The authors formulate the problem statement for randomly measuring with strong signal noise. The impact of white Gaussian signals noise on the recovery performance is analyzed to provide a theoretical basis for the reasonable design of the measurement matrix. With the idea that the measurement matrix can be adapted for noise suppression in the adaptive CS system, an adapted selective compressive sensing (ASCS) scheme is proposed whose measurement matrix can be updated according to the noise information fed back by the processing center. In terms of objective recovery quality, failure rate and mean-square error (MSE), a comparison is made with some nonadaptive methods and existing CS measurement approaches. Extensive numerical experiments show that the proposed scheme has better noise suppression performance and improves the support recovery of sparse signal. The proposed scheme should have a great potential and bright prospect of broadband signals such as biological signal measurement and radar signal detection.


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Cite this article

[IEEE Style]
F. Wen, G. Zhang and D. Ben, "Adaptive Selective Compressive Sensing based Signal Acquisition Oriented toward Strong Signal Noise Scene," KSII Transactions on Internet and Information Systems, vol. 9, no. 9, pp. 3559-3571, 2015. DOI: 10.3837/tiis.2015.09.015.

[ACM Style]
Fangqing Wen, Gong Zhang, and De Ben. 2015. Adaptive Selective Compressive Sensing based Signal Acquisition Oriented toward Strong Signal Noise Scene. KSII Transactions on Internet and Information Systems, 9, 9, (2015), 3559-3571. DOI: 10.3837/tiis.2015.09.015.