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Variable frequency-based multi-frame coherent track-before-detect method for weak tones in passive sonar.

Liu Zhang1,2, Shengchun Piao2,3,4, Junyuan Guo2,3,4

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This study introduces a novel variable frequency-based track-before-detect (TBD) method for enhanced passive detection of weak tones. The advanced particle filtering approach improves signal detection and frequency estimation accuracy, even with complex target maneuvers.

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Area of Science:

  • Signal Processing
  • Acoustic Detection

Background:

  • Passive detection of weak tones is challenging due to complex target maneuvers.
  • Existing multi-frame coherent integration and track-before-detect (TBD) methods have limitations in handling intricate tonal frequency variations, reducing coherent processing gain.

Purpose of the Study:

  • To propose a variable frequency-based multi-frame coherent track-before-detect (TBD) method to improve passive detection of weak tones.
  • To enhance adaptability for complex tonal frequency variations and reduce frequency estimation error.

Main Methods:

  • Modeling tonal frequency and phase evolution using polynomial functions within a state-space dynamical system.
  • Employing an improved particle filtering algorithm with data-adaptive sequential importance sampling for optimized particle distribution.
  • Analyzing optimal model order to minimize coherent gain loss.

Main Results:

  • The proposed method demonstrates improved detection performance compared to traditional approaches.
  • Significant reduction in frequency estimation error was observed.
  • High adaptability to complex tonal frequency variations was achieved.

Conclusions:

  • The variable frequency-based TBD method offers a robust solution for passive weak tone detection.
  • The particle filtering approach enhances signal processing capabilities in dynamic acoustic environments.
  • The method shows practical utility, validated by simulations and real-world experimental data (SwellEx-96).