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A graph-based narrowband matched-field source localization method.

Peng Xiao1, Jianmin Yang1

  • 1School of Marine Engineering and Technology, Sun Yat-sen University, Zhuhai, Guangdong, 519000, China xiaop36@mail.sysu.edu.cn, yangjm33@mail.sysu.edu.cn.

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This study introduces a novel graph-based matched field processing (MFP) method for underwater acoustic source localization. The new approach demonstrates improved accuracy and efficiency compared to traditional MFP techniques.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Underwater Acoustics

Background:

  • Matched Field Processing (MFP) is a key technique for underwater acoustic source localization.
  • Conventional MFP methods have limitations in accuracy and sensor requirements.

Purpose of the Study:

  • To integrate Graph Signal Processing (GSP) with narrowband Matched Field Processing (MFP).
  • To develop a more accurate and efficient underwater source localization method.

Main Methods:

  • Constructing a spatial adjacency matrix for arbitrary sensor distributions using Green's function.
  • Applying the graph Fourier transform for source localization within the GSP framework.

Main Results:

  • The graph-based MFP method shows superior accuracy compared to conventional MFP.
  • The proposed method requires fewer sensors for effective source localization.

Conclusions:

  • Combining GSP with MFP offers significant advantages for underwater acoustic source localization.
  • This novel approach enhances localization performance and reduces system complexity.