标题：A compressive signal detection scheme based on sparsity
作者：Qin, Shaohua ;Chen, Dongyan ;Huang, Xu ;Yu, Leilei
作者机构：[Qin, Shaohua ;Chen, Dongyan ;Huang, Xu ;Yu, Leilei ] School of Control Science and Engineering, Shandong University, China;[Qin, Shaohua ] College of 更多
来源：International Journal of Signal Processing, Image Processing and Pattern Recognition
摘要：Compressed sensing is a revolutionary technology in the research field of signal processing, which can reconstruct the sparse signal using fewer number of compressive measurements compared with conventional reconstruction methods. Compressed sensing can also be utilized to detect the sparse signal. However, the exact reconstruction operation is not necessary when the system aims to detect such sparse signal. Based on compressed sensing, a new compressive signal detection scheme using the sparsity order of the sparse signal is proposed in this paper. Compared with similar detection scheme using the supports of the sparse signal, the newly proposed scheme requires much fewer number of compressive samples. In particular, the proposed scheme does not require the support prior-information of the sparse signal. Simulation results verify the advantages of the proposed scheme and indicate that the new scheme can achieve better detection performance. © 2014 SERSC.