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Adaptive nulling array direction-of-arrival estimation based on adaptive kernel width mixture correntropy under

Si-Yuan Sun1,2,3, Liang Zhang1,2,3, Ze-Hua Dai4

  • 1National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China.

The Journal of the Acoustical Society of America
|December 5, 2025
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Summary
This summary is machine-generated.

This study introduces an adaptive algorithm for accurate direction-of-arrival (DOA) estimation in noisy underwater environments. The method enhances performance under limited data, improving underwater detection capabilities.

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Area of Science:

  • Underwater acoustics
  • Signal processing
  • Array signal processing

Background:

  • Impulsive noise in underwater environments challenges accurate direction-of-arrival (DOA) estimation.
  • Sources of noise include ice cracking, marine life, and sonar transmissions.
  • Existing algorithms struggle with performance under limited snapshots and impulsive interference.

Purpose of the Study:

  • To propose an efficient adaptive DOA estimation algorithm for practical underwater detection.
  • To address the limitations of current methods in handling impulsive noise and limited data.
  • To improve the accuracy and robustness of DOA estimation in challenging acoustic conditions.

Main Methods:

  • Integration of bias-compensated adaptive nulling array technology.
  • Application of an adaptive kernel width updating method based on mixture correntropy.
  • Adaptive kernel width optimization along the steepest gradient of prediction error for fast convergence.

Main Results:

  • The proposed algorithm demonstrates low steady-state error, even with limited snapshots.
  • Achieved high DOA estimation accuracy, low root mean square error, and improved resolution probability in simulations.
  • Validated robustness and effectiveness using real sea trial data.

Conclusions:

  • The developed adaptive algorithm effectively mitigates impulsive noise for improved DOA estimation.
  • The bias compensation and adaptive kernel width strategies ensure fast convergence and low error.
  • The algorithm shows significant promise for practical applications in underwater acoustic monitoring and detection.