浅海环境噪声垂直指向性探测海底参数

浅海环境噪声垂直指向性和海底地声参数密切相关,可以利用它来反演海底参数。本文在水平分层介质噪声场模型下,讨论了海底参数对噪声垂直指向性的敏感度,并假设半无限大液态海底,采用效率较高的自适应单纯形模拟退火算法全局寻优,根据中国某海区实测噪声数据,估计了海底声速、密度及衰减,分析了反演结果的不确定性。鉴于声速和密度在不同频率的反演结果不够一致,文中提出多频海底参数联合反演方法,提高了反演海底声学参数的精度。     

匹配垂直质点振速的浅海地声参数反演

海底声学参数对海洋波导中的声场特性研究和相关应用具有重要意义。针对一次夏季黄海声传播实验,分析了浅海负跃层环境下垂直质点振速的传播特性和简正波结构,说明当声源和接收器均位于负跃层下时,除海底附近外的大部分深度上垂直质点振速能量较高,且与声压相比,号数高的简正波对垂直质点振速的贡献更大,利用垂直质点振速进行匹配场反演能获得更高的海底参数敏感性。分析了海底吸收系数对垂直质点振速匹配场反演的影响,结果表明只有当进行匹配场反演时设置的海底吸收系数接近真实值时,才能获得准确的海底声速、密度和海深反演结果。利用实验中矢量水听器获取的垂直质点振速信号进行匹配场反演,将海底吸收系数在变化范围内取不同值对海底声速、密度和平均海深进行全局搜索,根据代价函数值最大确定了海底声速、密度及平均海深的反演结果,并利用不同距离上的声压传播损失反演出不同频率下的海底吸收系数。根据反演得到的海底声学参数计算声压传播损失,与实验中声压水听器测量结果符合较好。     

一种地声参数的联合反演方法

根据地声参数对不同声场物理量影响不同,提出了一种利用简正波频散特征结合声传播损失反演地声参数的联合反演方法。首先,考虑到简正波的频散特性(群速度)对海底的密度和声速较为敏感,而对海底吸收系数不敏感,利用自适应时频分析方法,获得不同频率不同号数简正波的到达时间差,以此作为代价函数,采用全局优化算法,反演出海底密度和海底声速的分层结构,并用概率统计的方法评价反演结果的有效性。反演出海底密度和声速后,利用实验船辐射噪声得到随距离连续的声传播损失来反演出海底吸收系数。最后,把反演的参数很好的用于声源匹配定位验证了反演结果的有效性。      

射线理论下的浅海环境噪声场空间相干性分析及海底声学参数反演

基于射线理论,以简化海底模型为基础,获得了浅海噪声场空间相干性在频域上的表示方法,并用于海底声学参数反演。将风关海洋噪声看作分布在无限大平面上的点源,通过计算噪声场垂直方向上的能量分布,进一步获得空间两点噪声场频域相干性表达式。利用数值仿真验证了模型对于不同海底类型的敏感性。并结合噪声场空间两点的频域相干性海上实验数据,反演得到该处海域的底质类型,进一步获得海底声速、密度和声衰减系数。结果表明,反演得到的海底参数与实际情况符合较好,文中提出采用的这种计算方法能够有效的反映海底反射对于噪声场空间相干性的影响,并且可在一定程度上提高反演海底声学参数效率。      

2005黄海实验混响垂直相关统计反演海底参数

处理并分析了2005黄海混响实验数据.在单层海底假设下利用300～800 Hz频段混响垂直相关数据反演了海底参数,并分析了参数反演结果的不确定性.结果发现:单频独立反演的声速值随频率增加而减小.类似的结果以前也有报道,导致难以有效地确定海底的平均声速.为了解决这一问题,本文假设海底具有两层分层结构,并提出了一种基于遗传算法的多频联合海底参数反演方法.同一海域声传播数据的简正波分离结果以及混响垂直相干实验值与基于反演参数计算的理论值吻合良好,验证了分层海底假设及参数反演结果的有效性.     

浅海地声参数的变维贝叶斯反演

为解决海底沉积层分层结构未知时的反演问题,提出了一种变维粒子滤波方法,利用声场的互谱密度,估计沉积层分层结构以及地声参数。仿真结果表明：变维粒子滤波在沉积层分层结构未知时,能有效反演沉积层层数以及地声参数,粒子的并行计算能使其相较于可逆跳蒙特卡洛马尔可夫链(rjMCMC)更加高效。利用变维粒子滤波,对南海垂直线阵列接收到的线性调频信号进行处理,反演结果与rjMCMC反演得到的沉积层层数和地声参数结果相近,说明了此方法能有效估计沉积层层数的同时反演浅海地声参数,得到可靠的参数后验概率密度。     

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.     

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。      

浅海声速剖面的匹配波束反演方法

为了快速反演获得浅海声速剖面,利用匹配波束构造了反演代价函数,在此基础上研究了浅海声速剖面的匹配波束反演方法(MBI)。并运用东中国海的实验数据进行实际反演,验证了MBI的可行性和鲁棒性。利用垂直线列阵接收的29个不同位置的爆炸声信号进行了声速剖面反演, MBI反演的结果与实验中直接测量的声速剖面一致,且反演声速剖面的均方根误差小于2 m/s。研究结果表明,MBI比常规匹配场反演(MFI)获得浅海声速剖面更快速、更准确,并且对底质参数的失配具有较高的鲁棒性。     

利用气枪声源数据的地声参数反演*

本文通过对东海采集的气枪声源数据进行处理,基于地声参数对不同声场观测量的敏感性差异,利用分步反演的策略进行分析。首先选择距离接收阵七个不同的距离点数据,通过warping变换准确提取第三阶至第八阶简正波的频散曲线;利用海底声速对频散曲线敏感的特性来反演声速;由Hamilton经验公式求得海底密度;通过传播损失拟合获得海底衰减。不同距离点数据反演的海底声速与密度一致性较高。实验提取的频散曲线和和反演参数仿真结果、实验获取的传播损失与反演参数获得传播损失均拟合较好。     

Bayesian geoacoustic inversion using wind-driven ambient noise

This paper applies Bayesian inversion to bottom-loss data derived from wind-driven ambient noise measurements from a vertical line array to quantify the information content constraining seabed geoacoustic parameters. The inversion utilizes a previously proposed ray-based representation of the ambient noise field as a forward model for fast computations of bottom loss data for a layered seabed. This model considers the effect of the array's finite aperture in the estimation of bottom loss and is extended to include the wind speed as the driving mechanism for the ambient noise field. The strength of this field relative to other unwanted noise mechanisms defines a signal-to-noise ratio, which is included in the inversion as a frequency-dependent parameter. The wind speed is found to have a strong impact on the resolution of seabed geoacoustic parameters as quantified by marginal probability distributions from Bayesian inversion of simulated data. The inversion method is also applied to experimental data collected at a moored vertical array during the MAPEX 2000 experiment, and the results are compared to those from previous active-source inversions and to core measurements at a nearby site.     

The effects of ignored seabed variability in geoacoustic inversion

Geoacoustic inversion using a matched-field inversion algorithm is a well-established technique for estimating the geoacoustic parameters of the seabed. This paper demonstrates how parameter estimation can be affected by unknown or wishfully ignored random range dependence of the true environment when the inversion model is--for practicality--assumed to be range independent. Simulations with controlled statistics were carried out using a simple shallow water model: an isospeed water column over a homogeneous elastic halfspace. The inversion parameters included water depth, compressional speed in the seabed, seabed density, and compressional wave attenuation. On average the environment is range independent: some parameters are constant while other parameters are random with range-independent means and variances. A Parabolic Equation underwater acoustic propagation model is used to calculate the simulated data fields for the range-dependent environment as well as to calculate the model fields for the range-independent inversion model. The Adaptive Simplex Simulated Annealing inversion algorithm is used to estimate the best-fit solution. It is found that ignoring the variability of even a single geoacoustic parameter leads to significant and correlated uncertainty (bias and variance) in the estimation of all inverted parameters. Results are presented for range variation of compressional sound speed and water depth.     

深海近距离声场频率-距离干涉结构反演海底声学参数

地声反演一般存在多解性的问题,不易有效分离沉积层声速与厚度,本文提出了一种当声源与接收水听器分别位于海面与海底附近时匹配声场干涉周期反演深海沉积层声速与厚度的方法。该声场周期结构由直达波与海底沉积层反射回波干涉形成,其干涉周期受沉积层声速和厚度影响,通过匹配实测与理论计算的声场干涉周期可有效反演沉积层声速和厚度。开展了深海实验验证,利用水听器接收到的近距离船舶噪声的声场干涉条纹,反演得到的实验海域海底沉积层声速与该海域海底表层采样平均值差小于20 m/s。数值仿真与实验结果表明该方法可以有效反演沉积层的声速与厚度。      

利用拖船自噪声进行浅海环境参数贝叶斯反演

研究了以拖船自噪声为参考声源的浅海环境参数反演问题,并针对反演结果不确定性快速量化评估问题,提出了一种基于自适应重要性抽样的贝叶斯反演新方法。反演利用了拖船自噪声低频线谱成分,并采用混合高斯推荐函数自适应推荐声场模型样本,使得样本集中于参数高概率密度区域,实现后验概率密度快速收敛计算。仿真试验结果表明:拖船自噪声反演能够准确估计水深、沉积层及阵列参数等。所提自适应重要性抽样贝叶斯反演方法的计算效率优于快速吉布斯抽样方法。利用试验数据处理验证,反演得到试验海域声学环境参数,计算传播损失与各阵元接收线谱强度变化吻合,说明反演最优环境模型能准确表征声场传播特征。      

Broadband sound propagation in shallow water and geoacoustic inversion

Part of an experiment to test a measurement package in a shallow water region in the Gulf of Mexico was designed to gather broadband acoustic data suitable for inversion to estimate seabed geoacoustic parameters. Continuous wave tow acoustic signals at multiple frequencies and broadband impulsive source signals were recorded on a horizontal line array in a high-noise environment. Simulated annealing with a normal mode forward propagation model is utilized to invert for a geoacoustic representation of the seabed. Several inversions are made from different data samples of two light bulb implosions, the measured sound speed profiles at the HLA and at the positions of the light bulb deployments, and for two different cost functions. The different cost functions, measured sound speed profiles, and measured time series result in different inverted geoacoustic profiles from which transmission loss is generated for comparison with measurements. On the basis of physical consistency and from the comparison of the transmission loss and time series, a best estimate geoacoustic profile is selected and compared to those obtained from previously reported inversions. Uncertainties in the sound speed profile are shown to affect the uncertainties of the estimated seabed parameters.     

Geoacoustic inversion based on reflection model of effective density fluid approximation

In order to obtain the physical and geoacoustic properties of marine sediments,an inverse method using reflection loss of different grazing angles is presented.The reflection loss is calculated according to the reflection model of effective density fluid approximation.A two-step hybrid optimization algorithm combining differential evolution and particle swarm optimization along with Bayesian inversion is employed in estimation of porosity,mean grain size,mass density and bulk modulus of grains.Based on the above physical parameters,geoacoustic parameters,including sound speed and attenuation,are further calculated.According to the numerical simulations,we can draw a conclusion that all the parameters can be well estimated with the exception of bulk modulus of grains.In particular,this indirect inverse method for bottom geoacoustic parameters performs high accuracy and strong robustness.The relative errors are 0.092%and 17%,respectively.Finally,measured reflection loss data of sandy sediments at the bottom of a water tank is analyzed,and the estimation value,uncertainty and correlation of each parameter are presented.The availability of this inverse method is verified through comparison between inverse results and part of measured parameters.     

Bayesian geoacoustic inversion of ship noise on a horizontal array

This paper applies geoacoustic inversion to low-frequency narrow-band acoustic data from a quiet surface ship recorded on a bottom-moored horizontal line array in shallow water. A Bayesian matched-field inversion method is employed which quantifies geoacoustic uncertainties and allows for meaningful comparison of inversion results from different data sets. Geoacoustic inversion results for ship-noise data are compared with inversion results for multitone data from a towed controlled source collected in the same experiment, and with independent geophysical measurements. To increase the information content of low-level ship-noise data, the effect of including multiple, independent data segments in the inversion is investigated and shown to significantly reduce geoacoustic parameter uncertainties. Geoacoustic uncertainties are also shown to depend on ship range and orientation, with increased uncertainties for long ranges and for the ship stern oriented away from the array.