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

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.