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中国科学院大学学报 ›› 2010, Vol. 27 ›› Issue (6): 794-799.DOI: 10.7523/j.issn.2095-6134.2010.6.010

• 论文 • 上一篇    下一篇

一种基于minimax准则的压缩采样信号检测方法

韩阔业1,2,3, 江海1,2,3, 王彦平1,2, 洪文1,2   

  1. 1. 中国科学院电子学研究所, 北京 100190;
    2. 微波成像技术国家级重点实验室, 北京 100190;
    3. 中国科学院研究生院, 北京 100190
  • 收稿日期:2010-03-05 发布日期:2010-11-15

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 Published:2010-11-15

摘要:

压缩感知理论是在已知信号具有稀疏性或可压缩性的条件下,对信号数据进行采集、编解码的新理论.压缩感知理论指出,当观测矩阵满足等容性原理时,可以通过远小于奈奎斯特采样点数的信号点数去重建原始信号.本文将压缩采样的框架应用到信号检测模型中去,提出了一种使用minimax准则对压缩采样的信号进行检测的方法,并从理论上证明了这种方法有很好的检测性能,最后采用蒙特卡罗仿真实验验证了理论分析的结果.

关键词: 信号检测, 压缩采样, 随机投影, minimax

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

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