哈尔滨工程大学学报2023，Vol.44Issue(11)：2044-2053,10.DOI:10.11990/jheu.202308004
联合匹配场和神经网络的声速时间场构建方法
A method for constructing a sound velocity time field by combining a matched field and neural network
摘要
Abstract
The variation in a local sound velocity field severely affects ocean acoustic positioning and navigation ac-curacy,and the construction of a high-precision and high-resolution sound velocity time field is particularly impor-tant.Aiming at the problem of the low accuracy of sound velocity field construction due to insufficient reference samples of the local sound velocity field,this paper establishes a construction method for a sound velocity time field based on the theory of a matched field and neural network.Matched field processing is adopted to simulate the sound velocity profile,using communication data and full water depth sound velocity profile data.Then,the sound velocity profile is constructed by a BP neural network fitting the EOF reconstruction coefficients and compared with the measured disposable temperature and salt depth profiler data.The results show that the root mean square error of MFPBP for simulating sound velocity profiles considering matched fields is 0.665 m/s,38.4％higher than 1.079 m/s for average sound velocity profiles.Therefore,the algorithm can improve the accuracy of constructing a sound velocity time field in complex marine environments.关键词
声速时间场构建/匹配场处理/后向传播神经网络/声速剖面反演/经验正交函数分解/启发式算法/射线声学理论/第一模态系数Key words
construction of sound velocity time field/matching field processing/BP neural network/inversion of sound velocity profile/empirical orthogonal function decomposition/heuristic algorithm/theory of ray acoustics/first modal coefficient分类
海洋学引用本文复制引用
李林洋,徐天河,王君婷,黄威,高凡,舒建旭..联合匹配场和神经网络的声速时间场构建方法[J].哈尔滨工程大学学报,2023,44(11):2044-2053,10.基金项目
崂山实验室科技创新项目(LSKJ202205104) （LSKJ202205104）
山东省自然科学基金项目(ZR2023QD163) （ZR2023QD163）
中国博士后科学基金项目(2023M732041) （2023M732041）
地理信息工程国家重点实验室基金项目(SKLGIE2022-ZZ2-02). （SKLGIE2022-ZZ2-02）
