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多波束测深中声速剖面的分层EOF自适应重构
引用本文:刘杨范,王振杰,赵爽.多波束测深中声速剖面的分层EOF自适应重构[J].声学技术,2020,39(3):372-378.
作者姓名:刘杨范  王振杰  赵爽
作者单位:中国石油大学(华东)地球科学与技术学院, 山东青岛 266555;中国石油大学(华东)地球科学与技术学院, 山东青岛 266555;海洋国家实验室海洋矿产资源评价与探测技术功能实验室, 山东青岛 266071
基金项目:国家重点研发计划(2016YFB0501700,2016YFB0501705);青岛海洋科学与技术国家实验室开放基金项目(QNLM2016ORP0401)
摘    要:在海水性质变化剧烈地区利用重构声速剖面进行多波束测深时,传统的经验正交函数(Empirical Orthogonal Functions,EOF)方法在阶次选取时未顾及声速浅水的复杂性和深水的平稳性的特点。针对传统EOF方法存在计算量大、精度低等问题,给出了一种声速剖面EOF重构中分层阶次的确定方法。根据常梯度声线跟踪计算深度,在满足0.25%倍水深限差的要求下,统计有效波束比,采用自适应方法确定出合理的阶次。实验结果表明,该方法相较于传统EOF重构声速剖面测深的阶次选取方法,降低了运算量,提高了精度。

关 键 词:声速剖面  经验正交函数(EOF)  分层  阶次选取  测深
收稿时间:2019/3/22 0:00:00
修稿时间:2019/5/19 0:00:00

Layered-EOFs based adaptive reconstruction of sound velocity profile in multi-beam sounding
LIU Yangfan,WANG Zhenjie,ZHAO Shuang.Layered-EOFs based adaptive reconstruction of sound velocity profile in multi-beam sounding[J].Technical Acoustics,2020,39(3):372-378.
Authors:LIU Yangfan  WANG Zhenjie  ZHAO Shuang
Affiliation:School of Geosciences, China University of Petroleum(East China), Qingdao 266580, Shandong, China;School of Geosciences, China University of Petroleum(East China), Qingdao 266580, Shandong, China;Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, Shandong, China
Abstract:In multi-beam sounding using reconstructed sound velocity profiles in the areas with significant variation of seawater properties, the complexity of shallow water and the stability of deep water are not taken into account for the function order selection of traditional empirical orthogonal function (EOF) method. Aiming at the problems of large computation amount and low accuracy of traditional EOF method, an approach to determining the orders of layered EOF for sound velocity profile reconstruction is presented in this paper. The depth is calculated by constant gradient ray tracing, and under the requirement of 0.25% depth difference, the effective beam ratio is counted and the reasonable orders are determined adaptively. The experimental results show that the proposed approach reduces the computational complexity and improves the accuracy compared with the sounding method using the traditional EOF-reconstructed sound velocity profile.
Keywords:sound velocity profile  empirical orthogonal function(EOF)  layering  order selection  sounding
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