海洋-声学耦合模式捕捉水声环境不确定性

考虑到海洋环境的时空变化对水声环境不确定性的影响,建立了海洋-声学耦合数值模式,实现了并行计算。该模式将声学计算纳入到运动的海洋中,从而实现了对水声环境的动态预报和估计。同时,采用集合预报方法对典型断面的温度垂直结构、实验海区声速剖面和传播损失进行预报,并给出了声速剖面的预报误差、不同深度与频率下,传播损失90%的概率区间以及声速、传播损失、声呐作用距离的不确定性直方图。结果反映了海洋时空变化对水声环境不确定性的影响,量化了水声环境中不确定性的大小。实验结果表明该方法可以刻画海洋动态变化引起的水声环境不确定性,并对其进行了量化和描述。     

海洋-声学耦合模式捕捉水声环境不确定性

考虑到海洋环境的时空变化对水声环境不确定性的影响,建立了海洋-声学耦合数值模式,实现了并行计算。该模式将声学计算纳入到运动的海洋中,从而实现了对水声环境的动态预报和估计。同时,采用集合预报方法对典型断面的温度垂直结构、实验海区声速剖面和传播损失进行预报,并给出了声速剖面的预报误差、不同深度与频率下,传播损失90%的概率区间以及声速、传播损失、声呐作用距离的不确定性直方图。结果反映了海洋时空变化对水声环境不确定性的影响,量化了水声环境中不确定性的大小。实验结果表明该方法可以刻画海洋动态变化引起的水声环境不确定性,并对其进行了量化和描述。      

界面参数估计及传播损失的射线声学预报

利用射线声学建立的海洋信道模型,根据给定海区声传播实验的实测数据,反演得到界面声学参数,并进行声传播损失预报。预报结果与实验数据比较表明,信道模型正确,界面参数选取与估计方法合理,传播损失预报性能良好。     

海洋—声学耦合过程不确定性快速预报

针对海洋声速空间非均匀和时变条件下的声场不确定性快速预报问题,根据海洋-声学耦合模式预报声速场时空变化过程,获取声速垂直结构不确定性分布规律,提出经验正交函数-随机多项式展开方法,以降低不确定参数维度,得到声场不确定性分布.数值计算表明该方法在保证同等精度的同时可大幅减少计算量,相比常规随机多项式展开方法计算效率可提高2个数量级,且计算量不随声速剖面复杂程度变化而改变.经海上实验验证,结果表明该方法可实现环境不确定性条件下的声场及其不确定性的快速预报。      

一种低声速沉积层海底参数声学反演方法

软泥底环境下沉积层参数的声学反演是国际水声领域的一个研究热点.浅海中,当高声速基底和海水之间存在一层低声速(小于海水声速)的沉积层时,小掠射角情况下不同频率声传播损失会出现周期性增大现象.基于此现象,提出一种适用于低声速沉积层的海底参数声学反演方法.首先,推导给出小掠射角情况下传播损失周期增大的频率间隔与沉积层声速、厚度及近海底海水声速之间的解析表达式;其次,利用一次黄海实验中软泥底环境下的宽带声传播信号,提取了小掠射角下传播损失增大的频率周期;再次,把该解析表达式作为约束条件,结合Hamilton密度与声速的经验公式,采用匹配场处理反演给出沉积层的声速、密度、厚度及基底的声速、密度;然后,利用声传播损失数据反演得到泥底环境下不同频率的声衰减系数,通过拟合发现泥底声衰减系数随频率近似呈线性关系;最后,给出了双层海底模型和半无限大海底模型等效性的讨论.反演结果为低声速沉积层海底声传播规律研究与应用提供了海底声学参数.     

海洋-声学耦合过程初始温度误差传递与发展

针对海洋初始温度场误差到水声传播误差的传递以及随时间演变发展的问题,优化海洋-声学耦合模式,通过对比遥感数据,验证了模型的可靠性。在此基础上,采用在控制试验温度初始场上加扰动的方法进行传播损失全局误差发展和区域误差发展试验。结果表明,初始温度场全局扰动在经过5天繁殖后使传播损失误差达到饱和,且扰动分布结构和海洋运动规律基本保持一致;对于在黑潮流域设定的目标海区,其上游区域的初始扰动发展最快。该结论可为开展海洋声学适应性观测提供依据。      

地声参数及传播损失不确定性估计与建模

地声参数的不确定性对水声传播具有重要的影响。通过贝叶斯理论建立水声环境不确定性推理模型,理论推导了地声参数的似然函数以及地声参数和传播损失的后验概率密度,并采用MCMC(Markov Chain Monte Carlo)进行了仿真计算,给出了地声参数的二维后验联合概率密度和一维边缘概率密度,在此基础上对传播损失的不确定性进行了估计,得到了传播损失80%的可信区间。仿真和实验结果表明,该方法适用于地声参数反演和不确定性估计,并能获取因地声参数不确定性导致的传播损失不确定性估计。     

南海北部负跃层环境下海底参数声学反演

利用2015年南海北部声学实验的实验数据,对海底声学参数进行反演。在综合分析声速起伏及海底模型对海底反演影响的基础上,通过选择等效的海水声速剖面和海底模型,改进了多参量联合地声反演方法,使得其不仅能解决反演中的多值性问题,还能适用于负跃层起伏环境下的声学反演。即当用匹配场反演海底声速和用传播损失反演海底衰减时,如果温跃层内有内波等随机起伏,可使用传播路径上平均声速剖面和单层等效海底进行声场计算。反演得到的海底声速和密度结果与海底采样测量符合较好,拟合给出了海底衰减系数随频率的非线性经验关系式。反演结果可为南海北部声传播规律研究与应用提供海底参数。      

浅海环境下数据同化声层析方法研究

讨论了适用于浅海的基于声速局部测量模型、声传播模型及声压场局部测量模型的声学数据同化方法,并给出了具体的执行算法。该算法根据最优化准则把局部声速和声压场的先验测量信息,以及声传播模型进行了有效地融合,提高了海洋环境参数估计的精度,为浅海声层析提供了新思路。同时,利用实验浅海声速测量数据,通过经验正交函数对实际海洋声速剖面进行了估计,并分析了各类噪声对水体声速场及海底声学参数估计精度的影响,验证了该执行算法的有效性。      

基于集合卡尔曼变换的东中国海声学 敏感区判定方法*

为改善海洋与水声环境预报质量,针对常规观测成本高、资料利用率低等问题,将适应性观测方法应用于海洋声学领域。结合海洋-声学耦合模式与集合卡尔曼转换敏感区诊断方法,以东中国海宫古海峡北部区域为验证区,计算并分析不同条件下海洋环境敏感区与声学敏感区分布,通过观测系统模拟试验验证适应性观测对验证区预报的提升效果。结果表明,两种敏感区位置随时间间隔增加均向验证区上游移动,海洋环境敏感区相比于声学敏感区分布更为集中,且平移特征更明显;对海洋环境敏感区和声学敏感区添加适应性观测均能提升海洋与水声环境的预报质量,提升效果随时间间隔增加而减小,在某种类型敏感区的适应性观测对相对应参数的预报质量提升效果优于对其他类型敏感区进行观测的效果。     

The rapid uncertainty prediction of the ocean-acoustic coupled model

Focusing on the rapid prediction of acoustic field uncertainty in environment with temporal and spatial sound speed perturbation, evolvement of sound speed structure over time is predicted based on the ocean-acoustic coupled model to obtain the uncertainty distribution of the vertical structure of sound speed. Further, a method combining the arbitrary polynomial chaos expansion with the empirical orthogonal function is proposed to reduce the dimensionality of uncertain parameters and to obtain the uncertainty distribution of the acoustic field. Simulations have shown that the computational complexity can be reduced by 2 orders of magnitude compared to the conventional polynomial chaos expansion while ensures the same precision.Moreover, the computational complexity is not influenced by the complexity of the sound speed profile. The acoustic field and uncertainty predicted in uncertain environment by proposed method also have been tested with the experimental data.     

Capturing uncertainties of the underwater acoustic environment based on an ocean-acoustic coupled model

Considering the uncertain effects of temporal and spatial changes in the marine environment on the underwater acoustic environment,we established an ocean-acoustic coupled numerical model and performed a parallel calculation.This model incorporated acoustic calculations into the dynamic ocean,thereby achieving a dynamic forecasting and assessment of the acoustic environment.Furthermore,we adopted the ensemble prediction method to predict the vertical structure of temperature in a classic cross-section,the sound speed of the cross-section of the investigated sea area,and transmission losses.We gave the prediction errors of the sound speed profile as well as the 90%probability interval of transmission losses and the uncertainty histograms of the sound speeds,transmission losses,and sonar ranges at different depths and frequencies.The results reflected the influence of marine temporal and spacial variations on the uncertainties of the underwater acoustic environment,and the results also quantified the uncertainties of the underwater acoustic environment parameters.The experimental results indicate that the method used in this study is able to delineate and quantify the uncertainties of the underwater acoustic environment caused by marine dynamic changes.     

浅海不确定声场的随机多项式展开法研究

为获得求解浅海不确定声场的普适模型,建立了随机多项式展开法与Helmholtz方程的非嵌入式耦合模型,其间运用概率配点法求解多项式系数。针对仅当海水深度不确定时的Pekeris波导、声速剖面和海深均不确定时的Pekeris波导以及下限深度不确定温跃层等几种情形,计算了传播损失概率密度分布。结果表明所建模型对声场计算模型普适性强,计算精度和计算效率高,可用于研究含多个不确定环境参数、声速剖面复杂的浅海环境中声传播的不确定性。      

Multiple-array passive acoustic source localization in urban environments

In many situations of interest, obstacles to acoustic wave propagation such as terrain or buildings exist that provide unique challenges to localization. These obstacles introduce multiple propagation paths, reflections, and diffraction into the propagation. In this paper, matched field processing is proposed as an effective method of acoustic localization in a two dimensional scattering environment. Numerical techniques can be used to model complex propagation in a space where analytical solutions are not feasible. Realistically, there is always some uncertainty in model parameters that in turn can adversely affect localization ability. In particular, uncertainty in array location, sound speed, and various parameters affecting inter-array coherence only are investigated. A spatially distributed, multiarray network is shown to mitigate the effects of uncertainty. Multiarray inverse filter processing techniques are evaluated through perturbation of uncertain model parameters. These techniques are more accurate and flexible to implement than other matched field processing methods such as time reversal.     

浅海复杂环境下等效声速剖面的构建方法*

针对浅海复杂环境声速剖面水平变化情况下的声传播损失预报及目标定位问题,提出了一种基于遗传算法的等效声速剖面重构算法。首先,将声速剖面进行时间和空间上的分解,从而将声速剖面抽象为对声速剖面前三阶正交函数系数的反演;其次,利用遗传算法,以先验声速剖面集为基础,进行参数反演。仿真结果表明,在浅海复杂条件下,传播损失预报受声速剖面及海洋参数的影响,不能直接运用接收或发射位置处的声速剖面进行传播损失预报,否则会对预报结果造成误差。通过构建具有声传播累积效应的等效声速剖面可以提高匹配场定位精度,完成目标定位,且在构建等效声速剖面时,接收位置处即本地声速剖面所占权重较大。     

Geoacoustic Inversion Based on a Vector Hydrophone Array

We propose a geoacoustic inversion scheme employing a vector hydrophone array based on the fact that vector hydrophone can provide more acoustic field information than traditional pressure hydrophones. Firstly, the transmission loss of particle velocities is discussed. Secondly, the sediment sound speed is acquired by a matchedfield processing （MFP） procedure, which is the optimization in combination of the pressure field and vertical particle velocity field. Finally, the bottom attenuation is estimated from the transmission loss difference between the vertical particle velocity and the pressure. The inversion method based on the vector hydrophone array mainly has two advantages： One is that the MFP method based on vector field can decrease the uncertain estimation of the sediment sound speed. The other is that the objective function based on the transmission loss difference has good sensitivity to the sediment attenuation and the inverted sediment attenuation is independent of source level. The validity of the inverted parameters is examined by comparison of the numerical results with the experimental data.     

Pekeris waveguide comparisons of methods for predicting acoustic field amplitude uncertainty caused by a spatially uniform environmental uncertainty (L)

Acoustic field calculations in underwater environments are often uncertain because the environmental parameters required for such calculations are uncertain. This letter compares the accuracy of direct simulations, the field shifting approximation, and polynomial chaos expansions for predicting acoustic amplitude uncertainty in 100-m-deep Pekeris waveguides having spatially uniform uncertain water-column sound speed. When this sound speed is Gaussian-distributed with a standard deviation of 1 m/s, direct simulations and polynomial chaos expansions, based on 21 field calculations, are more accurate than the field shifting approximation, based on two field calculations. This ranking reverses as the sound-speed standard deviation increases to 20 m/s.