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Fenghua Li1, Feilong Zhu1, Yanjun Zhang1

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Summary
This summary is machine-generated.

This study introduces a new method to improve adaptive matched field processing (AMFP) for detecting moving targets in shallow waters. The technique effectively mitigates source motion, enhancing target detection ranges.

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Area of Science:

  • Underwater acoustics
  • Signal processing
  • Oceanography

Background:

  • Adaptive matched field processing (AMFP) is challenged by source motion in shallow water environments.
  • A large number of samples is needed for AMFP to minimize covariance matrix variance, but this blurs sound interference for moving targets.

Purpose of the Study:

  • To present a novel source motion mitigation technique for broadband moving targets in shallow water acoustics.
  • To enhance the performance of adaptive matched field processing (AMFP) in the presence of target movement.

Main Methods:

  • The proposed technique applies waveguide invariant theory to reformulate the covariance matrix.
  • Frequency and phase shifting are used, guided by a single scalar parameter hypothesis.
  • A moving target is effectively rendered stationary when the hypothesis parameter matches the true value.

Main Results:

  • The source motion mitigation technique was applied to experimental data from a bottom-mounted horizontal line array.
  • The method demonstrated a significant increase in target detection ranges.
  • Improved ability of AMFP to produce a sharp main peak for moving targets.

Conclusions:

  • The developed technique effectively mitigates source motion challenges in shallow water AMFP.
  • This advancement improves the detection capabilities for moving underwater targets.
  • The findings suggest practical improvements for sonar systems operating in dynamic environments.