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Frequency-Domain Second-Order Decorrelation with Compact Time-Domain Regularization for Convolutive Underwater

Huapeng Cao1, Tingting Yang1,2, Qi He3

  • 1School of Navigation, Dalian Maritime University, Dalian 116026, China.

Sensors (Basel, Switzerland)
|July 15, 2026
PubMed
Summary

This study enhances underwater acoustic source separation using frequency-domain second-order decorrelation (FSD) with compact time-domain regularization. Results show improved performance in complex, noisy environments, optimizing FSD for better underwater signal recovery.

Keywords:
ShipsEarBSS benchmarkblind source separationjoint diagonalizationtime-domain constraintunderwater acoustic propagation

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Area of Science:

  • Underwater Acoustics
  • Signal Processing
  • Machine Learning

Background:

  • Classical algorithms struggle with long-delay multipath and low signal-to-noise ratios in underwater acoustic mixtures.
  • Spectral overlap from mechanical and biological sources further complicates signal separation.
  • Existing methods like FastICA and JADE are limited by degraded higher-order statistical cues.

Purpose of the Study:

  • To adapt frequency-domain second-order decorrelation (FSD) for convolutive underwater acoustic mixtures.
  • To introduce a simulated benchmark (ShipsEarBSS) for evaluating source separation algorithms.
  • To optimize FSD configurations for improved underwater acoustic signal recovery.

Main Methods:

  • Adapted FSD using multi-block joint diagonalization of cross-power spectral density matrices in the short-time Fourier transform domain.
  • Implemented compact time-domain regularization for demixing filters.
  • Utilized the ShipsEarBSS benchmark with simulated multichannel mixtures and known reference sources.

Main Results:

  • An optimized compact FSD configuration demonstrated improved performance compared to baseline methods (frozen FSD, PCA-SVD, AuxIVA).
  • Compact time-domain regularization positively impacted the FSD operating point under the ShipsEarBSS protocol.
  • Filter length, CPSD block count, and output ordering were found to be empirical configuration choices.

Conclusions:

  • Compact time-domain regularization is beneficial for FSD in underwater acoustic environments.
  • The effectiveness of specific FSD configuration parameters (filter support, block count, output ordering) is context-dependent.
  • The ShipsEarBSS benchmark provides a valuable tool for evaluating underwater acoustic source separation techniques.