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Frequency-unknown matched field processing for frequency estimation and localization.

Xian Yan1,2,3,4, Shengchun Piao1,2,3,4, Qian Tong1,2,3,4

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Summary
This summary is machine-generated.

Frequency-unknown matched field processing (FU-MFP) estimates source frequency and location using signal inversion. This advanced method improves upon conventional MFP, especially in low signal-to-noise ratio environments.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Oceanography

Background:

  • Matched field processing (MFP) traditionally requires known source frequencies.
  • Unknown source frequencies necessitate estimation from received signals.
  • Conventional MFP struggles with unknown frequency and low signal-to-noise ratio (SNR) conditions.

Purpose of the Study:

  • To develop and evaluate frequency-unknown matched field processing (FU-MFP).
  • To enhance source localization and frequency estimation in challenging acoustic environments.
  • To improve performance in low SNR conditions.

Main Methods:

  • Incoherent FU-MFP incorporates inversion of transmission frequency and radial velocity for motion compensation.
  • Coherent FU-MFP combines passive synthetic aperture processing with motion compensation.
  • Extended Fourier transform windows are utilized through radial velocity inversion.

Main Results:

  • FU-MFP successfully estimates source frequency and location in low SNR.
  • Coherent FU-MFP achieves localization using weak line spectrum signals.
  • Simulations and experiments demonstrate FU-MFP significantly outperforms conventional MFP.

Conclusions:

  • FU-MFP provides robust source localization and frequency estimation.
  • The proposed coherent FU-MFP method is effective for weak signals in low SNR.
  • This technique offers a significant advancement over traditional MFP for unknown frequency scenarios.