Comprehensive Study of Inversion Methods for Sound Speed Profiles in the South China Sea

Traditional acquisition method of sound speed profiles using hydro-acoustic instruments is accurate but time-consuming and costly.To overcome this problem,some inversion methods have been developed over the last few decades.In this study,a comprehensive comparison of two inversion methods–the acoustic inversion method(AIM)and the satellite observation reconstruction method(SOR)–is presented.For AIM,the sound speed profile is first parameterized by the empirical orthogonal function(EOF)and the optimal parameters are searched by simulated annealing algorithm with respect to the cross-correlation function of the receiving signal and the simulation signal.For SOR,remotely sensed data are used to construct sound speed profiles.An experiment was conducted in the northeast of the South China Sea to verify the two methods.Both methods can obtain sound speed profiles quickly and cheaply.Compared with the sound speed profiles obtained by a conductivity-temperature-depth(CTD)instrument,the root-meansquare-error(RMSE)of AIM is 0.55 m s^(−1) and that of SOR is 1.71 m s^(−1).It is clear that AIM provides better inversion performance than SOR.Another primary benefit of AIM is that this method has no limitation to the inversion depth.The simulation results of sound propagation in regard to the inversed sound speed profiles show that the transmission losses of AIM and CTD are consistent and that of SOR is adversely affected by the inversion error of the sound speed and the inversion depth.But SOR has particular advantages in the inversion coverage.Together,all of these advantages make the AIM particularly valuable in practice.

Reconstructing Sound Speed Profiles with Sea Surface Data

Ocean sound speed profile(SSP) is the key factor affecting acoustic propagation. The acquisition of SSPsin real time with high precision is meaningful for underwater activities. By means of the remote sensing method, thesea surface data could be obtained in near-real time. Typically, the subsurface fields are correlated with the sea surfaceparameters. Thus, the SSPs could be obtained by means of satellite remote sensing. In this paper, the history as wellas the current research over the reconstruction of subsurface fields by means of sea surface data is introduced. Thentwo methods to reconstruct the SSPs with sea surface data, including the linear regression method using the empiricalorthogonal function, and the self-organizing method based on the big data theory, are described in detail in the paper.

Centimeter‑level‑precision seafloor geodetic positioning model with self‑structured empirical sound speed profile

In-field Sound Speed Profile(SSP)measurement is still indispensable for achieving centimeter-level-precision Global Navigation Satellite System(GNSS)-Acoustic(GNSS-A)positioning in current state of the art.However,in-field SSP measurement on the one hand causes a huge cost and on the other hand prevents GNSS-A from global seafloor geodesy especially for real-time applications.We propose an Empirical Sound Speed Profile(ESSP)model with three unknown temperature parameters jointly estimated with the seafloor geodetic station coordinates,which is called the 1st-level optimization.Furthermore,regarding the sound speed variations of ESSP we propose a so-called 2nd-level optimization to achieve the centimeter-level-precision positioning for monitoring the seafloor tectonic movement.Long-term seafloor geodetic data analysis shows that,the proposed two-level optimization approach can achieve almost the same positioning result with that based on the in-field SSP.The influence of substituting the in-field SSP with ESSP on the horizontal coordinates is less than 3 mm,while that on the vertical coordinate is only 2–3 cm in the standard deviation sense.

利用低声速沉积层反射特性线性反演地声参数

为提高反演效率和降低地声参数耦合,提出一种线性反演低声速沉积层地声参数的方法。从类线性声速剖面的两层海底平面波反射系数出发,分析了全透射角及全透射角下最大反射损失、干涉条纹等反射特性与各相关地声参数的关系,并构建了相应的代价函数。结合敏感性分析和分步反演策略,分步反演了低声速沉积层地声参数。该方法适用于低声速沉积层声速梯度恒定的情况。利用新英格兰泥地实验部分海底反射损失数据进行了实验验证。实验反演结果与相关跨维反演结果基本一致,反演误差分别为声速比0.1%,密度比0.3%,吸收系数14.6%,声速梯度为15.8%。反演效果显示,该方法一定程度上规避了部分地声参数间的耦合,且可给出决定类线性声速剖面形状的幂次项的最佳估计。

基于BP神经网络的非等效声速剖面反演

声速剖面反演基于历史数据获取声速剖面,是海洋环境声层析中的一种方法。传统声速剖面反演法很难获取大面积海域的非等效声速剖面,得出的结果一般都是等效声速剖面。为解决该问题,提出一种基于反向传播(Back Propagation,BP)神经网络的非等效声速剖面反演方法。对比结果表明,该方法能有效反演非等效声速剖面并且反演结果相比传统声速剖面反演具有更高的精度。

Tracking of time-evolving sound speed profiles with an auto-regressive state-space model

An approach for time-evolving sound speed profiles tracking in shallow water is discussed. The inversion of time-evolving sound speed profiles is modeled as a state-space estimation problem, which includes a state equation for predicting the time-evolving sound speed profile and a measurement equation for incorporating local acoustic measurements. In the paper, auto-regression （AR） method is introduced to obtain a high-order AR evolution model of the sound speed field time variations, and the ensemble Kalman filter is utilized to track the sound speed field. To validate the approach, the accuracy in sound speed estimation is analyzed via a numerical implementation using the ASIAEX experimental environment and the sound velocity measurement data. Compared with traditional approaches based on the state evolution represented as a random walk, simulation results show the proposed AR method can effectively reduce the tracking errors of sound speed, and still keep good tracking performance at low signal-to-noise ratios.

A methodology to achieve the basis function for the expansion of sound speed profile

In order to evaluate the reliability and applicability of the Empirical Orthogonal Functions（EOFs）in the acoustic inversion of sound speed profile（SSP）and reduce EOF＇s dependence on the sample data,a methodology is proposed for the achievement of the basis functions for SSP＇s expansion.By analyzing the oceanographic dynamics which is the main cause of the SSP＇s variation,the basis functions are obtained naming the Hydrodynamic Normal Modes（HNMs）.The HNM basis functions are almost the same as those derived from the EOF method,while HNMs has less dependence on the amount of the sample data.HNMs method has a physically meaningful interpretation,and it could give out the physical parameters which determine the basis functions for the expansion of SSP,and this makes it possible to analyze and evaluate the trustiness and applicability of EOFs.

水下声速场构建方法综述

实时、精确地构建区域声速场是建设水下综合定位、导航、授时与通信体系的重要组成部分。本文梳理并分析了水下声速场构建领域的研究现状,总结了声速剖面直接测量方法与反演方法。声速反演法相比于直接测量法具有更高的便捷性和可接受的精度性能。然而,声速反演方法依赖于声呐观测数据,因此难以适用于无水下观测系统覆盖的地区,并且无法对未来时刻的声速分布进行预测。如何在无声场观测数据情况下,综合利用历史先验信息进行智能化、高精度地全海深声速场构建,弹性化为水下用户提供不同精度、实时性需求的声速分布估计服务,是未来声速场构建研究主流趋势。

基于声线到达时差的浅海声速剖面反演

提出了采用声线到达单个水听器到达时间差反演浅海声速剖面的方法，并给出了具体算法。根据仿真观测数据，采用该方法反演得到声速剖面与声速剖面真值之间误差的均方根为＝1.04 m/s、平均值为1．87 m/s。研究结果表明该反演方法可以用于反演浅海声速剖面。

一种新的声速剖面结构参数化方法

在Munk模型和GDEM模型的基础上,提出了一种新的声速剖面结构参数化模型,即分层声速剖面模型(LSSPM)。模型用含9个参数的四层分段函数分别描述混合层、主跃层、深海声道层和深海等温层的声速结构,形式简明、直观。数值实验结果表明,LSSPM模型对声速剖面的拟合可达到较高的精度,且对于中国周边的深海和浅海区域有较好的适用性。

台湾以东海域声速剖面序列的EOF分析

利用了4 a的Argo剖面序列,通过经验正交函数（EOF）分析,得出了台湾以东海域声速垂直结构的时空变化特征。EOF拟合声速剖面的精度与选取的模态数有关,合成剖面时包含的模态数越多,精度越高;前3-6个模态反映了海区声速结构的主要变化,累积方差贡献率可达89.4%-96.6%。第1模态描述了声速在垂直方向上的同相变化,具有年周期,峰值和谷值分别出现在夏季和冬季;第2模态描述了声速在近表层与次表层和主跃层的反相变化。第1、2模态的共同作用是声速垂直结构差异的主导因素,使近表层声速的季节性变化较大,而主跃层的变化相对较小;而第3模态及更高阶的模态对声速剖面的调制作用在物理意义上并不明显。

浅水声速剖面的反演方法与实验验证

提出一种在浅水域进行声速剖面反演的方法。通过将某地浅水声速剖面用经验正交函数(EOF)进行表示 ,利用一个很短的垂直线列阵接收声源信号 ,估计信号的多途到达角结构 (DOA) ,以到达角结构的误差为代价函数 ,对实测的声速剖面进行了反演。实验结果表明

菲律宾海的声速剖面结构特征及季节性变化

应用Argo资料研究了菲律宾海的声速剖面结构特征。通过统计分析得到了合理的跃层标准,分析了主跃层、季节性跃层和表面正梯度层的区域性分布及季节性变化。结果表明,菲律宾海主要受赤道流系和北太平洋西边界流系的支配,其环流结构和水团配置对声场结构影响很大;主跃层的经向差异显著,但季节性变化较小,其平均位置由南向北逐渐加深,强度逐渐减弱;季节性跃层的分布主要受混合层的季节性变化以及北部海区冬季温跃层通风过程的影响,夏季较强较厚,冬季较弱较薄;深海声道轴季节性变化较小,南极中层水和北太平洋中层水的温盐差异是其经向变化的主要原因。综合考虑海区声速结构的区域性和季节性特征,将其归纳为6种典型结构,得出了各类声速剖面的模态特征及垂直结构参数的统计特征值。

中国近海声速剖面的模态特征

利用WOA05数据集提供的气候态声速场数据,通过模糊C-均值聚类分析,得到了中国近海声速剖面模态特征的区域性分布和季节性变化。结果表明,中国近海的声速剖面结构可分为深海型(D型)、浅海型(S型)和过渡型(T型)三个基本类型。深海型剖面为"季节性跃层/正梯度+主跃层+深海声道+深海正梯度"结构,南海和菲律宾海因所属水系不同呈现出明显差异;浅海型剖面季节性变化强烈,冬季为正梯度或均匀型结构,其它季节为"混合层+季节性跃层+下均匀层"结构,负梯度强度与季节性跃层的变化有关,在夏季达到最强;过渡型剖面形态与邻近的深海型上层结构类似,但因受地形制约产生与深海型不同的声传播特征。海面太阳辐射、海洋环流、混合层以及水团配置的季节性变化导致的温盐场空间分布差异是造成不同海区、不同季节声场速剖面结构差异的根本原因。

深海声速剖面结构变化对会聚区偏移特性的影响分析

应用分层声速剖面模型(LSSPM)和BELLHOP高斯束声场计算模型,对深海声速剖面结构变化引起的会聚区偏移特性进行了分析。结果表明,声速值的整体变化对会聚区影响很小,而混合层、主跃层、深海等温层及声道轴的变化都会使会聚区位置出现不同程度的偏移。主跃层是上层海洋变化的主要体现,混合层变化对会聚区的影响也是通过改变主跃层的形态结构实现的,跃层强度的增大使会聚区向远离声源方向偏移。深海等温层的声速变化体现了深海水团的结构差异,与主跃层引起的会聚区偏移呈反相变化。声道轴附近的声速变化体现了不同类型中层水团侵入和混合的影响,所引起的会聚区偏移反映了声道轴上层与下层梯度变化的综合效应,声速最小值的增加使会聚区向远离声源方向偏移。

声跃层结构变化对深海汇聚区声传播的影响

根据射线理论建立了线性声速结构条件下的声跃层强度与深海汇聚区关系模型,用最小位移角讨论了海洋环境变化(如声跃层强度变化、声跃层位置变化及季节性跃层生消等)与汇聚区距离和宽度变化的相关性.结果表明,声跃层的结构变化对汇聚区特征影响很大.声跃层强度增大使汇聚区向远离声源的方向变化,跃层强度每增加0.01 s-1对应的汇聚区位移增大约为3.5～5.0 km.声跃层位置变化对汇聚区的影响小于声跃层强度,与两层结构的声速剖面相比,上行结构使汇聚区向靠近声源的方向变化,声跃层上升200 m对应的汇聚区位移减小约为1.0～1.5 km,声跃层越浅,汇聚区距离越近;下行结构使汇聚区向远离声源的方向变化,混合层加深200 m对应的汇聚区位移增大约为1.0～1.5 km,混合层越深,汇聚区距离越远.季节性跃层的生消使近表层有负梯度、零梯度和正梯度的变化.负梯度结构的变化规律与两层结构条件下的声跃层强度变化类似,但对汇聚区的影响程度相对较小;正梯度结构使汇聚区在近表层出现表面声道,梯度值的增强将使汇聚区向靠近声源的方向变化.

由传播时间反演海水中的声速剖面

海水中的声速剖面对声传播有比较重要的影响.利用海上实验的实际数据由声信号的传播时间反演海水中的声速剖面.用经验正交函数表示声速剖面,根据选取的代价函数应用遗传算法搜索最优解.为了提高反演算法的性能,快速反演获得海水中的声速剖面,在射线声学理论下,对传播时间的计算方法进行了改进,有效降低了算法的计算量.利用海上实验的实际数据反演获得的声速剖面与实验时直接测量获得的声速剖面相比较,误差小于2‰.反演结果与实测结果基本相符.

基于自组织神经网络的声速剖面分类方法研究

利用自组织神经网络技术,结合声速剖面特点,研究了声速剖面的描述方法、网络中神经元个数的确定、获胜神经元的邻域及其邻域内神经元的拓扑关系等对网络结构和声速剖面类别划分的影响,给出了分类声速剖面的网络构造思想和神经网络结构。实验验证了该方法的正确性。

浅海中沉积层参数对多途到达时差反演声速剖面的影响

本文以简正波模型和声线模型为基础,通过计算机仿真,研究了浅海多途到达时延差结构与沉积层密度、声速、传播损失系数等参数的关系。针对100m左右浅海和600－1300Hz的信号频率,对两种模型仿真结果进行了比较。结果表明,声线模型仿真得到的多途到达时延差结构与简正波模型仿真的结果基本一致。沉积层参数失配对基于声线模型的多途到达时差反演SSP的影响为:反演声速剖面的均方根误差的变化小于1.45m/s,平均误差的变化小于2．60m/s。这说明,在所使用的频段内,浅海沉积层参数对多途到达时差反演浅海声速剖面的影响不大,工程应用中可以忽略不计。

循环神经网络在浅海声速-声源联合反演中的应用

利用序贯滤波对时变声速剖面进行反演追踪,通常会将声速剖面的时变特性描述为一阶随机游走过程。为了使状态方程更好的预测状态变量的走向,本文利用循环神经网络学习历史水文数据,对浅海环境下的时变声速剖面进行建模,利用集合卡尔曼滤波进行对声速剖面的反演,并对声源进行定位。结果相较于使用一阶随机游走过程的联合反演结果误差更小,在声源深度上均方根误差有着80%的降低,声速剖面反演结果误差有着38.2%的降低。本文通过实测声速剖面的仿真声学数据验证了该方法的可行性。