内孤立波环境下稳健降阶自适应匹配场定位方法研究

The mismatch of sound speed induced by internal solitary waves will cause the inaccurate estimation in the matched field processing for source localization. In this paper, a robust Adaptive Matched Field Processing method of Rank Reduction (RR-AMFP) for internal solitary waves is proposed. Based on the traditional adaptive matched field processing algorithm, this method integrates dominant mode rejection beamforming, and reduces the rank of sampling covariance matrix by eigen-decomposition, and suppresses the noise space. Meanwhile, a suppressing coefficient and a weighting factor are used to calculate the weight vector in the matching process, and the mismatched coping vectors are detected. Therefore, this method can maintain better robustness in the internal solitary wave environment, and the reduction of rank also shortens the calculation time. The simulation results show that this method can accurately estimate the source location under a single internal solitary wave, but the internal solitary wave train with large amplitude will still lead to more errors of estimation. The estimated distance error is 3.3% and depth error is 1.5% in the localization experiment of internal solitary waves in the South China Sea, which belongs to reliable localization. The experiment results demonstrate the effectiveness of the method in the actual environment with internal solitary waves.