Inversion for sound speed profile in shallow water based on long short-term memory networks and ray theory  

作　　者：WU Longhao LIU Song WU Zhaozhi PAN Caineng YUAN Fei 

机构地区：[1]Key Laboratory of Underwater Acoustic Communication and Marine Information Technology Ministry of Education(Xiamen University),Xiamen 361005

出　　处：《Chinese Journal of Acoustics》2025年第1期1-17,共17页声学学报(英文版)

基　　金：supported by the National Natural Science Foundation of China(62371404,62271425,62071401).

摘　　要：To address the problem of underwater sound speed profile(SSP)inversion in underwater acoustic multipath channels,this paper combines deep learning and ray theory to propose an inversion method using a long short-term memory(LSTM)network.Based on the equidistant characteristics of the horizontal line array,the proposed method takes the sensing matrix composed of multi-modal data,such as time difference of arrival and angle of arrival,as input,and utilizes the ability of the LSTM network to process timeseries data to mine the correlations between spatially ordered receiving array elements for sound speed profile inversion.On this basis,a time delay estimation method based on hard threshold estimation method and cross-correlation function is proposed to reduce the measurement errors of the sensing matrix and improve the anti-multipath performance.The feasibility and accuracy of the proposed method are verified through numerical simulations.Compared with the traditional optimization algorithm,the proposed algorithm better captures the nonlinear characteristics of SSP,with higher inversion accuracy and stronger noise resistance.

关 键 词：Sound speed profile Long short-term memory network Underwater acoustic multipath channel Time delay estimation 

分 类 号：TN9[电子电信—信息与通信工程]