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A signal detection method via compressive sampling using minimax criterion
Received date: 2010-03-05
Online published: 2010-11-15
Compressed sensing theory is a novel data collection and coding theory under the condition that signal is sparse or compressible. It has been shown that when the measurement matrix satisfies RIP, the original signal can be reconstructed with observations which are far less than Nyquist rate samples. In this paper, we apply the compressed sampling scheme to a signal detection model and propose a detection method based on compressive sampling using minimax criterion. Theoretical analysis shows that this method can achieve good detection performance, which is also verified by Monte Carlo experiments.
Key words： signal detection; compressive sampling; random projections; minimax
HAN Kuo-Ye , JIANG Hai , WANG Yan-Ping , HONG Wen . A signal detection method via compressive sampling using minimax criterion[J]. Journal of University of Chinese Academy of Sciences, 2010 , 27(6) : 794 -799 . DOI: 10.7523/j.issn.2095-6134.2010.6.010
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