Noise Reduction Method for Acoustic Sensor Arrays in Underwater Noise

Abstract

Noise reduction capacity in sensor array signal processing is derived under the assumption of white noise, where the noise reduction is defined as the difference between the input noise power and the output noise power in this paper. However, the underwater noise mainly includes white noise and correlated noise. In this situation, the noise reduction capacity may be deteriorated considerably in actual underwater environment. To tackle this problem, a new noise reduction method, which is named imaginary delay-and-sum beamforming method, is proposed. First, the noise signals received by a sensor array are decomposed into symmetrical and asymmetrical components. Theoretically, the symmetrical component can only affect the real parts of the noise covariance matrix. Then, the real parts of the data covariance matrix are eliminated to reduce the symmetrical noise, and the beamforming is completed by using only imaginary parts. The output signal-to-noise ratio is improved and the root mean square error of the direction-of-arrival estimation is decreased. Theoretical analyses and experimental results show that the proposed method can be easily implemented to improve the noise reduction capacity in sensor array signal processing.