Sparse signal recovery with OMP algorithm using sensing measurement matrix

Guan Gui, Abolfazl Mehbodniya, Qun Wan, Fumiyuki Adachi

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)285-290
Number of pages6
JournalIEICE Electronics Express
Issue number5
Publication statusPublished - 2011


  • Compressed sensing (CS)
  • Mutual incoherent property (MIP)
  • Orthogonal matching pursuit (OMP)
  • Sensing measurement matrxi (SMM)
  • Sparse signal recovery

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Electrical and Electronic Engineering


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