采用邻域近似算法估计环境参数不确定性

根据贝叶斯理论,逆问题的解可以用后验概率密度来表征,它包含了模型参数先验知识和观测数据信息,反映了反演参数的不确定性.一种快速吉布斯采样算法已经被用于后验概率密度的多维积分运算,但其需要调用大量的声场前向模型,在多个频率或水平变化的匹配场参数反演中,计算量仍然很大.基于邻域近似算法,提出一种比快速吉布斯采样算法更快的参数不确定性估计方法.对低维参数反演问题,邻域算法可以很好地逼近真实的后验概率密度;而对高维问题及其敏感参数,在模型参数样本量有限的条件下,邻域算法很难精确地估计后验概率密度.为了克服以上缺点,并完整地得到反演参数的不确定性信息,设计了一种多步估计方案.数值仿真和实测数据分析表明,多步邻域算法采用较少的计算代价,可获得与快速吉布斯方法相似的估计精度.     

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。      

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。     

利用Bayesian-MCMC方法从雷达回波反演海洋波导

应用贝叶斯-蒙特卡罗（Bayesian-MCMC）方法将海洋波导参数的先验信息描述为先验概率密度,结合雷达回波资料（电磁波传播损耗）,得到待反演海洋波导参数的后验概率密度,用马尔可夫链蒙特卡罗（MCMC）-Gibbs采样器采样后验概率密度分布,并用样本最大似然估计值作为对海洋波导参数分布的估计.数值实验结果表明,该方法对先验信息进行了有效利用,反演精度高于遗传算法的反演精度.该方法较为充分利用先验信息,得到解的概率分布,即解的不确定性分析,这在实际应用中有一定的参考价值. 关键词： 波导 电磁波传播损耗 贝叶斯-蒙特卡罗 概率分布     

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。     

动态水声环境不确定性的预报与估计

水声环境具有强烈的时空易变性,为了解其变化中的规律和产生的不确定性,将POM海洋数值模型和水声传播模型FOR3D进行耦合,建立海洋—声学耦合数值模式。对海区的温盐等环境参数和水下声场进行预报,给出了典型断面的温度垂直结构、实验海区声速剖面和传播损失。同时,采用集合卡尔曼滤波(EnKF)方法结合海洋—声学耦合数值模式分析了水声环境的不确定性,对不同深度与频率下,传播损失的均值与满足90%的可能区间进行了计算,同时给出了不同点声速、传播损失、声纳作用距离的不确定性直方图。和实验数据的对比结果表明该方法具有较高的有效性,能对水声环境的不确定性进行合理的预报与估计。     

浅海水声信道冲激响应空变特性研究

浅海声传播对空间参数的变化十分敏感,信道冲激响应随空间的变化使水声信号处理的性能受到很大限制。文中采用射线理论模型估计信道冲激响应,用互相关方法仿真计算了信道响应对空间参数的敏感性,并对信道冲激响应空变特性的实际应用进行了讨论。     

舰船辐射噪声贝叶斯方法反演浅海底层结构及地声参数EI北大核心CSCD

针对以舰船辐射噪声为参考声源的浅海海底分层结构及地声参数反演问题,研究了一种基于贝叶斯理论的浅海多层海底地声参数反演方法。反演中以舰船辐射噪声的线谱成分为研究对象,进而采用非线性贝叶斯反演方法反演浅海底层结构、层中声速、声速衰减和密度,并对反演结果的不确定性进行分析。反演结果的最大后验概率估计值和边缘概率分布分别通过拨正模拟退火算法和Metropolis-Hastings采样法在各参数先验区间内计算获得,并根据贝叶斯信息准则确定最佳海底分层结构。海上实验表明:根据该方法反演获得海底分层结构及地声参数,计算得到的声压场与实测舰船辐射噪声传播损失误差不超过10%,反演结果能够准确表征实验海区海底特征。反演结果不确定性分析表明:海底纵波声速、横波声速以及密度的不确定性更小,对声压场变化更加敏感,反演结果更有效、准确。     

联合简正波水波和底波频散特性的贝叶斯地声参数反演

大多数基于浅海简正波模态频散数据的地声参数反演方法无法对深层底质声学参数进行可靠估计,究其原因是仅利用了简正波水波频散特征,忽略了与深层底质声学参数密切相关的底波频散特征,因此,本文在分析了包含水波和底波的浅海宽带数据的基础上,结合底波频散特征对深层底质声学参数变化更加敏感的物理特性,实现了基于完整简正波频散特性的贝叶斯地声参数反演,并针对简正波宽带声场模型计算复杂度较高的现实问题,利用变分贝叶斯蒙特卡罗方法的推断优势,完成了未知参数的可靠估计和快速后验分析.仿真和海上实验结果表明:联合简正波水波和底波频散特征数据的贝叶斯地声参数反演,不仅可以有效估计深层底质声学参数,而且降低了其他相关环境参数的估计不确定性.     

基于等效密度流体近似反射模型反演海底参数

为了获取海底沉积物的物理和地声特性,根据等效密度流体近似反射模型得到的不同掠射角下的海底反射损失,利用差分进化算法和粒子群算法相结合的两级混合优化算法以及Bayesian反演方法对海底沉积物的孔隙度、平均颗粒粒度、颗粒质量密度以及颗粒体积弹性模量进行反演,再根据这4个物理参数的估计值进一步计算出海底地声参数,包括声速和衰减。通过反演结果与仿真真值的比较可以看出,除颗粒体积弹性模量外,得到的估计结果是令人满意的,特别是这种间接反演海底地声参数的方法对地声参数的估计具有较高的精确性和较强的稳健性,相对误差分别为0.092%和17%。最后,对实验室水池池底沙质沉积物的反射损失数据进行处理,给出了沙质沉积物各参数的估计值、不确定性和相关性,并通过反演结果与部分实测参数值的比较验证了反演方法的可行性。     

Multi-step geoacoustic inversion with a towed line array

Geoacoustic inversion is important for acoustic field predictions and matched field localizations in shallow water.Combing the Matched-field inversion(MFI) and the Reflectionloss inversion,a multi-step Bayesian inversion for geoacoustic parameters was presented.This method applied the posterior probability density(PPD) or inversion results from one inversion as prior information for subsequent inversion.First,the sensitive parameters were determined by the MFI.Second,the insensitive parameters were determined by the Reflection-loss inversion based on the PPD and inversion results from the MFI.The PPD results indicated that the multi-step inversion method was performed better than direct matched-field inversion,and the inversion results of some parameters were improved significantly.To demonstrate the advantages of the multi-step inversion method on the sound field prediction,the statistical properties of transmission loss based on the posterior probability were introduced.The transmission loss distribution showed that the predicted acoustic fields based on the multi-step inversion method had smaller errors.     

Statistical estimation of transmission loss from geoacoustic inversion using a towed array

Geoacoustic inversion estimates environmental parameters from measured acoustic fields (e.g., received on a towed array). The inversion results have some uncertainty due to noise in the data and modeling errors. Based on the posterior probability density of environmental parameters obtained from inversion, a statistical estimation of transmission loss (TL) can be performed and a credibility level envelope or uncertainty band for the TL generated. This uncertainty band accounts for the inherent variability of the environment not usually contained in sonar performance prediction model inputs. The approach follows [Gerstoft et al. IEEE J. Ocean. Eng. 31, 299-307 (2006)] and is demonstrated with data obtained from the MAPEX2000 experiment conducted by the NATO Undersea Research Center using a towed array and a moored source in the Mediterranean Sea in November 2000. Based on the geoacoustic inversion results, the TL and its variability are estimated and compared with the measured TL.     

利用浅海声场干涉条纹反演海底参数方法研究

浅海频散特性导致声场在距离-频率平面形成干涉条纹,该干涉条纹蕴含着声源以及海底信息。本文通过降噪、滤波等方法,提取船舶辐射噪声干涉条纹中距离域干涉准周期、波导不变量以及去扩展衰减系数(不考虑扩展损失后接收到噪声级随距离的衰减程度)三种特征量的观测值,基于无限均匀沉积层海底模型,采用简正波计算程序理论计算上述三种特征量作为拷贝,提出一种以模拟退火法作为搜索寻优策略的新的匹配反演海底参数的方法。海试数据处理结果表明,该方法反演估计所得海底密度、声速、衰减系数三参数用于浅海负跃层条件下的声场预报效果比较良好。     

Maximum entropy approach to statistical inference for an ocean acoustic waveguide

A conditional probability distribution suitable for estimating the statistical properties of ocean seabed parameter values inferred from acoustic measurements is derived from a maximum entropy principle. The specification of the expectation value for an error function constrains the maximization of an entropy functional. This constraint determines the sensitivity factor (β) to the error function of the resulting probability distribution, which is a canonical form that provides a conservative estimate of the uncertainty of the parameter values. From the conditional distribution, marginal distributions for individual parameters can be determined from integration over the other parameters. The approach is an alternative to obtaining the posterior probability distribution without an intermediary determination of the likelihood function followed by an application of Bayes' rule. In this paper the expectation value that specifies the constraint is determined from the values of the error function for the model solutions obtained from a sparse number of data samples. The method is applied to ocean acoustic measurements taken on the New Jersey continental shelf. The marginal probability distribution for the values of the sound speed ratio at the surface of the seabed and the source levels of a towed source are examined for different geoacoustic model representations.     

Effects of incoherent and coherent source spectral information in geoacoustic inversion

This paper examines the effect on matched-field geoacoustic inversion of including source spectral information, as can be available in controlled-source acoustic surveys. Source information can consist of relative or absolute knowledge of the source amplitude and/or phase spectra, and can allow frequency-coherent processing of spatial acoustic-field data. A number of multi-frequency acoustic processors, appropriate for specific types of source information, are defined based on the likelihood function for complex acoustic-field data with Gaussian noise. The information content of the various processors is quantified in terms of marginal probability distributions and highest-probability density intervals for the unknown geoacoustic and geometric parameters, which define the accuracy expected in inversion. Marginal distributions are estimated using a fast Gibbs sampler approach to Bayesian inversion, which provides an efficient, unbiased sampling of the multi-dimensional posterior probability density. The analysis is illustrated for incoherent and coherent processors corresponding to several types of source knowledge ranging from complete information to no information, and the results are considered as a function of the spatial and frequency sampling of the acoustic fields.     

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.     

Uncertainty estimation in simultaneous Bayesian tracking and environmental inversion

This paper develops a Bayesian approach for two related inverse problems: tracking an acoustic source when ocean environmental parameters are unknown, and determining environmental parameters using acoustic data from an unknown (moving) source. The formulation considers source and environmental parameters as unknown random variables constrained by noisy acoustic data and by prior information on parameter values (e.g., physical limits for environmental properties) and on inter-parameter relationships (limits on radial and vertical source speed). The goal is not simply to estimate parameter values, but to rigorously determine parameter uncertainty distributions, thereby quantifying the information content of the data/prior to resolve source and environmental parameters. Results are presented as marginal posterior probability densities (PPDs) for environmental parameters and joint marginal PPDs for source ranges and depths. Given the numerically intensive inversion, an efficient Markov-chain Monte Carlo importance-sampling approach is developed which combines Metropolis and heat-bath Gibbs' sampling, employs efficient proposal distributions based on a linearized PPD approximation, and considers nonunity sampling temperatures to ensure a complete parameter search. The approach is illustrated with two simulated examples representing tracking a quiet submerged source and geoacoustic inversion using noise from an unknown ship of opportunity. In both cases, source, seabed, and water-column parameters are unknown.     

基于等效密度流体模型的地声参数分析

目前的地声参数反演多采用液态海底模型,但是实际海底为多孔弹性海底。该文在等效密度流体模型基础上,通过计算液态海底和多孔弹性海底的反射系数及传播损失,给出了等效密度流体模型和液态海底模型的等效性分析。数值仿真结果表明在低频情况下,多孔弹性海底给出的快纵波声速与等效密度流体模型给出的声速以及等效密度流体的实部与真实的海底密度基本一致。将等效密度流体模型近似看作液态海底模型进行反射系数和传播损失计算,在小掠射角和远距离时,计算结果表明与多孔弹性海底计算结果具有较好一致性,从而以此为依据确定海底为液态,进行地声参数反演。