Sparse signal recovery with OMP algorithm using sensing measurement matrix
Sparse signal recovery with OMP algorithm using sensing measurement matrix
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DOI：
10.1587/elex.8.285
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发表时间：
2011-03-10
影响因子：
0.8
通讯作者：
Adachi, Fumiyuki
中科院分区：
文献类型：
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作者：
Gui, Guan;Mehbodniya, Abolfazl;Adachi, Fumiyuki
基于随机测量矩阵的正交匹配追踪（OMP）算法，由于随机测量矩阵列间的相干干扰，常导致变量选择错误。在本文中，我们提出了一个感知测量矩阵（SMM）-OMP，减轻相干干扰，从而提高信号的成功恢复概率。结果表明，SMM-OMP选择稀疏信号的所有重要变量之前，选择不正确的。我们提出了一个基于互不相干特性（MIP）的理论分析，以验证所提出的方法具有更好的性能比RMM-OMP。各种仿真结果证实了我们提出的方法的效率。
Orthogonal matching pursuit (OMP) algorithm with random measurement matrix (RMM), often selects an incorrect variable due to the induced coherent interference between the columns of RMM. In this paper, we propose a sensing measurement matrix (SMM)-OMP which mitigates the coherent interference and thus improves the successful recovery probability of signal. It is shown that the SMM-OMP selects all the significant variables of the sparse signal before selecting the incorrect ones. We present a mutual incoherent property (MIP) based theoretical analysis to verify that the proposed method has a better performance than RMM-OMP. Various simulation results confirm our proposed method efficiency.