Welcome to Journal of University of Chinese Academy of Sciences,Today is

›› 2010, Vol. 27 ›› Issue (6): 794-799.DOI: 10.7523/j.issn.2095-6134.2010.6.010

• Research Articles • Previous Articles     Next Articles

A signal detection method via compressive sampling using minimax criterion

HAN Kuo-Ye1,2,3, JIANG Hai1,2,3, WANG Yan-Ping1,2, HONG Wen1,2   

  1. 1. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
    2. National Key Laboratory of Microwave Imaging Technology, Beijing 100190, China;
    3. Graduate University, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2010-03-05 Online:2010-11-15

Abstract:

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

CLC Number: