Efficient Adaptive Beamforming of Underwater Acoustic Target under Impulsive Noise

Abstract

Underwater target detection is seriously affected by underwater impulse noise. In general, it is considered that the environmental noise follows Gaussian distribution. However, the underwater marine environmental noise data show that there is large impulse noise in underwater random noise, such as ice fracture in polar underwater environment and underwater impulse noise caused by iceberg collision and extrusion. At present, most beamforming methods are optimal in Gaussian environment noise, and their performance is greatly reduced in impulse noise environment. When the actual noise is impulse noise, the performance of conventional beamformer in impulse noise environment will be greatly reduced. To solve these problems, an adaptive beamforming method based on Andrew's sine estimator is proposed in this paper. The Andrew's sine function is a robust estimator, which has been used in outlier handling and robust statistics. However, such superior estimator does not receive attention in the field of adaptive beamforming. In this paper, a new variable parameter Andrew's sine estimator has been designed to improve performance. Simulation experiments demonstrate that the proposed adaptive beamforming method still has good beamforming performance in impulse noise environment. And the proposed method has been compared with the traditional beamforming algorithms to verify its performance.