Reverberation suppression method for active sonar systems using non-negative matrix factorization with pre-trained frequency basis matrix

Geunhwan Kim, Seokjin Lee

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In active sonar systems, detection always suffers from reverberation interference from multiple scatterers in oceanic environments; therefore, numerous studies have been conducted on reverberation suppression. Recently, a non-negative matrix factorization (NMF)-based method was proposed and successfully applied to reverberation suppression. However, the conventional NMF-based method makes convergence challenging because the frequency basis matrix is initialized without considering reverberation characteristic information from oceanic environments. To solve these problems, We propose an improved NMF-based reverberation suppression method adopting a pre-trained reverberation basis matrix and modified sparse update rule. The proposed method is evaluated by analyzing simulation and sea experiment data and the study confirmed that the detection performance was improved compared to the conventional method under various signal-to-reverberation ratio conditions. Several topics are also discussed to analyze the proposed method in detail.

Original languageEnglish
Pages (from-to)148060-148075
Number of pages16
JournalIEEE Access
Volume9
DOIs
StatePublished - 2021

Keywords

  • Active sonar
  • Non-negative matrix factorization
  • Pre-trained basis matrix
  • Reverberation suppression
  • Sparseness

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