A Blind Recovery Algorithm for Spectrum-sparse Signals Sub-Nyquist Sampling

摘要：

Wideband analog signals push contemporary analog-to-digital conversion systems to their performance limits. The recent development of compressive sensing theory enables direct analog-toinformation conversion of sparse (or compressible) signals at sub-Nyquist rate. In this paper, we implement spectrum-sparse signals sub-Nyquist sampling by use of Modulated Wide Converter (MWC). To overcome the drawback of requiring exact sparsity of the existing recovery algorithm, we introduce the Sparsity Adaptive Matching Pursuit (SAMP) method into reconstruction stage to search the support set of unknown signal vectors blindly. The numerical experiments demonstrate that the MWC system with the proposed recovery algorithm can implement spectrumsparse signals sub-Nyqiust sampling and perfect reconstruction under the condition of not knowing exact sparsity.

关键词： sub-Nyquist sampling Blind recovery sparse multiple measurement vectors

作者: Jianxin Gai Ziquan Tong Shuang Cheng Junjie Wang Xu Liu

作者单位: The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Hei The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Hei

会议类型: 国际会议

会议名称: The 6th International Forum on Strategic Technology(IFOST 2011)(第六届国际战略技术论坛)

会议地点: 哈尔滨

会议语种:英文

页码: 754-757

在线出版日期: 2011-08-22（万方平台首次上网日期，不代表论文的发表时间）