Geoacoustic Information Content of Horizontal Line Array Data

This paper examines the effectiveness of horizontal line arrays (HLAs) for matched-field inversion (MFI) by quantifying geoacoustic information content for a variety of experiment and array factors, including array length and number of sensors, source range and bearing, source-frequency content, and signal-to-noise ratio (SNR). Emphasis is on bottom-moored arrays, while towed arrays are also considered, and a comparison with vertical line array (VLA) performance is made. The geoacoustic information content is quantified in terms of marginal posterior probability distributions (PPDs) for model parameters estimated using a fast Gibbs sampler approach to Bayesian inversion. This produces an absolute, quantitative estimate of the geoacoustic parameter uncertainties which can be directly compared for various experiment and array factors.     

Quantifying data information content in geoacoustic inversion

This paper examines the information content in matched-field geoacoustic inverse problems as a function of a variety of experiment factors, with the aim of guiding data collection and processing to achieve the best possible inversion results. The information content of the unknown geoacoustic parameters is quantified in terms of their marginal posterior probability distributions, 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. When sampled to convergence, the marginal distributions are found to have simple, smooth shapes that facilitate straightforward comparisons. The approach is general; the specific examples considered here include factors such as the number of sensors in the receiving array, array length, source-receiver range, source frequency, number of frequencies, source bandwidth, and signal-to-noise ratio     

Estimating geoacoustic parameters using matched-field inversion methods

In this paper, we use matched-field inversion methods to estimate the geoacoustic parameters for three synthetic test cases from the Geoacoustic Inversion Techniques Workshop held in May 2001 in Gulfport, MS. The objective of this work is to use a sparse acoustic data set to obtain estimates of the parameters as well as an indication of their uncertainties. The unknown parameters include the geoacoustic properties of the sea bed (i.e., number of layers, layer thickness, density, compressional speed, and attenuation) and the bathymetry for simplified range-dependent acoustic environments. The acoustic data used to solve the problems are restricted to five frequencies for a single vertical line array of receivers located at one range from the source. Matched-field inversion using simplex simulated annealing optimization is initially used to find a maximum-likelihood (ML) estimate. However, the ML estimate provides no information on the uncertainties or covariance associated with the model parameters. To estimate uncertainties, a Bayesian formulation of matched-field inversion is used to generate posterior probability density distributions for the parameters. The mean, covariance, and marginal distributions are determined using a Gibbs importance sampler based on the cascaded Metropolis algorithm. In most cases, excellent results were obtained for relatively sensitive parameters such as wave speed, layer thickness, and water depth. The variance of the estimates increase for relatively insensitive parameters such as density and wave attenuation, especially when noise is added to the data.     

Bayesian geoacoustic inversion for the Inversion Techniques 2001 Workshop

This paper applies a Bayesian formulation to range-dependent geoacoustic inverse problems. Two inversion methods, a hybrid optimization algorithm and a Bayesian sampling algorithm, are applied to some of the 2001 Inversion Techniques Workshop benchmark data. The hybrid inversion combines the local (gradient-based) method of downhill simplex with the global search method of simulated annealing in an adaptive algorithm. The Bayesian inversion algorithm uses a Gibbs sampler to estimate properties of the posterior probability density, such as mean and maximum a posteriori parameter estimates, marginal probability distributions, highest-probability density intervals, and the model covariance matrix. The methods are applied to noise-free and noisy benchmark data from shallow ocean environments with range-dependent geophysical and geometric properties. An under-parameterized approach is applied to determine the optimal model parameterization consistent with the resolving power of the acoustic data. The Bayesian inversion method provides a complete solution including quantitative uncertainty estimates and correlations, while the hybrid inversion method provides parameter estimates in a fraction of the computation time.     

两种基于贝叶斯点估计理论的多声源定位方法研究

海洋环境参数失配是制约匹配场定位性能的主要因素之一。为了克服环境失配,本文基于贝叶斯理论,将环境参数与声源的距离和深度一起作为未知量进行反演。然而在进行多声源定位时,反演参数的维数几何增长,极大地增加了反演问题的复杂性和计算量。为此本文将声源强度和噪声方差表示成其极大似然估计值,从而将这些参数进行隐式采样,大大降低了反演的维数和难度。文章比较了两种贝叶斯点估计方法,最大后验概率密度方法和最大边缘后验概率密度方法。最大后验概率密度方法的解是令后验概率密度取得最大值的参数组合,可以利用优化算法快速获得。最大边缘后验概率密度法将其他参数积分,得到目标参数的一维边缘概率分布,分布的最大值为反演结果。该方法得到最优估计值的同时可以获取参数估计的不确定信息。在环境参数和声源参数都未知的情况下,利用蒙特卡洛法在不同信噪比情况下对两种声源定位方法进行分析,实验结果表明：(1)对于敏感参数,如声源距离、水深和海水声速,最大边缘后验概率密度法比最大边缘后验概率密度方法的性能好。(2)对于较不敏感的参数,如海底声速、海底密度和海底声衰减,当信噪比较低时,最大边缘后验概率密度方法能较好地平滑噪声,从而比最大边缘后验概率密度法具有更好的性能。由于声源距离和深度是敏感参数,研究表明最大边缘后验概率密度法提供了一种在不确知环境下更可靠的多声源定位方法。     

消频散变换反演海底地声参数

提出1种将消频散变换应用到海底地声参数反演的方法。对单一水听器接收声压信号进行消频散处理后,根据群延时差建立代价函数,反演得到主要海底参数,最后根据贝叶斯统计理论给出了待反演地声参数的边缘后验概率密度。对单层波导进行仿真证明这种新方法的有效性。     

Geoacoustic model parameter estimation using a bottom-moored hydrophone array

This paper describes results from an experiment carried out to investigate geoacoustic inversion with a bottom-moored hydrophone array located in the shallow waters of the Timor Sea off the northern coast of Australia. The array consisted of two arms in a V shape, horizontally moored at a site that was essentially flat over a large area. Hydrophone positions were estimated using an array element localization (AEL) technique that established relative uncertainties of less than 1 m on the seafloor. The data used for geoacoustic inversion were from experiments with continuous wave (CW) tones in the 80- to 195-Hz band transmitted from a towed projector. A hybrid search algorithm determined the set of geoacoustic model parameters that maximized the Bartlett fit (averaged coherently spatially at each tone and incoherently over frequency) between the measured and modeled data at the array. Due to the long range experimental geometry, the inversion was sensitive to attenuation in the sediment. The inverted geoacoustic profile performed well in a simple test for localizing the sound source at other sites in the vicinity of the array. Range-depth localization performance for the horizontal array was comparable to that for an equivalent vertical array.     

Estimation of Transmission Loss in the Presence of Geoacoustic Inversion Uncertainty

A common problem in sonar system prediction is that the ocean environment is not well known. Utilizing probabilistic based results from geoacoustic inversions we characterize parameters relevant to sonar performance. This paper describes the estimation of transmission loss and its statistical properties based on posterior parameter probabilities obtained from inversion of ocean acoustic array data. This problem is solved by first finding an ensemble of relevant environmental model parameters and the associated posterior probability using a likelihood based inversion of the acoustic array data. In a second step, each realization of these model parameters is weighted with their posterior probability to map into the transmission loss domain. This approach is illustrated using vertical-array data from a recent benchmark data set and from data acquired during the Asian Seas International Acoustics Experiment (ASIAEX) 2001 in the East China Sea. The environmental parameters are first estimated using a probabilistic-based geoacoustic inversion technique. Based on the posterior probability that each of these environmental models fits the ocean acoustic array data, each model is mapped into transmission loss. This enables us to compute a full probability distribution for the transmission loss at selected frequencies, ranges, and depths, which potentially could be used for sonar performance prediction.     

不确定海洋环境中基于贝叶斯理论的多声源定位算法

环境参数失配导致定位性能大幅度下降是匹配场定位所面临的难题之一。应用贝叶斯理论对环境聚焦,是当前解决该难题的研究热点。环境聚焦方法的实质是将未知环境参数和声源位置联合优化估计,当出现多个目标时,估计的参数会随着声源个数成倍增加,因此不得不利用有限的观测信息来实现众多参数的估计。本文采用最大似然比方法,获得信号源谱和误差项的最大似然估计,实现这些敏感性较弱参数的间接反演,有效降低了反演参数维数和定位算法复杂度。针对遗传算法的早熟和稳定性差的问题,改进了似然函数的经验表达式。将多维后验概率密度在参数起伏变化范围内积分,得到反演参数的一维边缘概率分布,求解最优值的同时进行反演结果的不确定性分析。本文仿真了位于相同距离、不同深度的两个声源,使用仿真实验验证了提出算法的有效性。     

Matched-field geoacoustic inversion of low-frequency source tow data from the ASIAEX East China Sea experiment

Geoacoustic inversion results based on data obtained during the Asian Seas International Acoustics Experiment (ASIAEX) 2001 East China Sea experiment are reported. The inversion process uses a genetic-algorithm-based matched-field-processing approach to optimize the search procedure for the unknown parameters. Inversion results include both geometric and geoacoustic variables. To gauge the quality of the inversion, two different analyses are employed. First, the inversion results based upon discrete source-receiver ranges are confirmed by continuous source localization over an interval of time. Second, separate inversions at many different ranges are carried out and the uncertainties of the parameter estimation are analyzed. The analysis shows that both methods yield consistent results, ensuring the reliability of inversion in this study.     

Matched-field inversion for geoacoustic model parameters in shallowwater

Matched-field inversion is used to, estimate geoacoustic properties from data obtained in an experiment with a vertical line array (VLA). The experiment was carried out using broad-band sources (shots) in water depths of about 200 m on the continental shelf off Vancouver Island. The data were processed to obtain spectral components of the field for frequencies near the bubble frequency for the shot. The ocean bottom in this region consists of a layer of mainly sandy sediments (about 100 m thick) overlying older consolidated material. Consequently, the inversion was designed to estimate the parameters of a two-layer elastic sediment model. In the inversion, an adaptive global search algorithm was used to investigate the multidimensional space of geoacoustic models in order to determine the set of values corresponding to the best replica field. Convergence is driven by adaptively guiding the search to regions of the parameter space associated with above-average values of the matched field correlation between the measured and replica fields. The geoacoustic profile estimated by the inversion consisted of a 125-m layer with compressional speed ~1700 m/s and shear speed ~400 m/s, overlying a layer with compressional speed ~1900 m/s. This model is consistent with the results from conventional seismic experiments carried out in the same region     

Geoacoustic inversion of tow-ship noise via near-field-matched-field processing

This paper discusses geoacoustic inversion from tow-ship noise data acquired via a horizontal towed array. Through simulations and experimental results, it is shown that even very quiet ships radiate sufficient noise power to enable self-noise inversion of basic geoacoustic parameters such as effective bottom velocity. The experimental results presented are particularly encouraging in view of the high level of interference shown to be tolerated from nearby shipping.     

Data Uncertainty Estimation in Matched-Field Geoacoustic Inversion

This paper examines a variety of approaches to treating unknown data uncertainties in matched-field geoacoustic inversion. Both optimal parameter estimation via misfit minimization and parameter uncertainty estimation via Gibbs sampling are considered. The misfit is based on the likelihood function for Gaussian-distributed errors, which requires specification of the data variance at each frequency. Unfortunately, independent knowledge of variance is rarely available due to unknown theory errors. Many applications of matched-field minimization implicitly assume that variance effects are uniform over frequency; however, this can be a poor assumption as theory errors generally vary with frequency. Parameter uncertainty estimation to date has used fixed maximum-likelihood (ML) variance estimates, which does not account for the variance uncertainty in estimating parameter uncertainties. This paper considers two new approaches to treating data uncertainty in matched-field inversion: Including variances explicitly as additional (nuisance) parameters in the inversion, and treating variances as implicit unknowns by constraining the misfit according to an ML variance formulation (this includes variance uncertainty without increasing the number of unknown parameters). All of the above approaches are compared for realistic synthetic test cases and for shallow-water acoustic data measured in the Mediterranean Sea as part of the PROpagation channel SIMulator experiment (PROSIM'97).     

An investigation of algorithm-induced variability in geoacoustic inversion

This paper investigates the inherent variability in the results of matched-field geoacoustic inversion algorithms. This algorithm-induced variability must be considered when interpreting inversion results in terms of environmental changes as a function of time or space. Fast simulated annealing (FSA), genetic algorithms (GA), and a hybrid algorithm (adaptive simplex simulated annealing; ASSA) are compared by performing multiple inversions of benchmark synthetic data (noise free and noisy) and acoustic data measured over both low- and high-speed sea-bed sediments in the MAPEX 2000 experiment. ASSA produced the lowest variability in inversion results for all cases, followed by GA and FSA. For the high-speed MAPEX 2000 case, the variability is essentially negligible, while for the low-speed case the variability is significant as compared with environmental variations reported in the literature.     

浅海聚焦定位中简化地声模型的应用研究

为了提高定位算法的环境宽容性,聚焦法将环境参数纳入了寻优空间。聚焦法虽然降低了对环境测量的要求,但是反演参数的增加也增加了反演的复杂性。基于海底反射特性,用两个参数对海底进行建模。通过标准的反演测试问题对简化地声模型在浅海聚焦定位中的有效性进行了分析。结果表明:基于简化地声模型的聚焦定位是可行的。在获得正确定位结果的同时,随着地声参数个数的减少,匹配场处理的便捷性得到了提高。文中引入的简化地声模型是聚焦问题中参数最少的地声模型,它可以有效减少聚焦定位参数维数以提升反演的便捷性。同时,简化地声模型在参数敏感性和耦合性上有较好的表现,这些优点可以保证定位结果的稳健性。     

Phenomenological and global optimization inversion

This paper discusses geoacoustic inversion results based on benchmark range-dependent data using SAGA, a global inversion package, and using phenomenological inversions. In phenomenological inversions, physical and signal-processing approaches are used to enhance the data to extract specific features. The global optimization approach is carried out on complex-valued vertical array data, transmission loss data, and reverberation data. The importance of checking the solution is emphasized by inspecting the match with the data and the error estimates and by checking the solution using data that has not been used in constructing the solution. The results show that we are able to estimate the geoacoustic parameters and that these parameters could be used to predict the field for different frequencies and/or source-receiver geometry than used in the inversion.     

A Sound Approach to Soft Sediment Resolution

The last few years has seen a surge in research activities directed towards investigating properties and dynamics of young marine, limnic and fluvial sediments. It is by now a well established fact that the sequence of sediments ranging from concentrated benthic suspension over fluid mud to un-consolidated material summarized as liquid sediments (LS), act as carriers for a wide range of pollutants discharged or migrated into waterways. Knowledge of the transport and fate of LS allows determining the transport and fate of adsorbed constituents (e.g., heavy metals, pesticides, PCBs, PAHs). To assess the environmental impact of LS, efforts have to be made to better understand the processes in relation to hydrodynamics and the chemical and physical properties of the layers. Since physical laws limit the resolution and detection power of conventional seismo-acoustic systems in respect of LS, alternative measurement, data analysis and processing approaches have to be found. Adapted acoustic procedures initially developed for shallow water marine environments to extreme shallow water regimes using matched field inversion techniques can reveal geoacoustic parameters including density, compressional wave speed and attenuation as a function of depth and time. The paper outlines the effects of sediment mobility upon the environment followed by a short overview of techniques commonly used to investigate sediments and other freshwater/marine events. The problems faced and limitations of existing systems are briefly outlined. Results obtained with recently developed and refined geoacoustic inversion methods are presented highlighting their potential for long-term study of physical properties and dynamics of LS.     

Benchmarking geoacoustic inversion methods using range-dependent field data

Over the past decade, inversion methods have been developed and applied to acoustic field data to provide information about unknown ocean-bottom environments. An effective inversion must provide both an estimate of the bottom parameters and a measure of the uncertainty of the estimated values. This paper summarizes results from the Office of Naval Research (ONR)/Space and Naval Warfare Systems Command (SPAWAR) Geoacoustic Inversion Techniques Workshop, test cases 4 and 5. The workshop was held to benchmark present-day inversion methods for estimating geoacoustic profiles in shallow water. The format of the workshop was a blind test to estimate unknown geoacoustic profiles by inversion of measured acoustic transmission loss data in octave bands and reverberation envelopes. The data sets for test cases 4 and 5 were taken at two locations in shallow water, one in the East China Sea and the other along the southwest coast of Florida. The limitations of the data and the limits to the knowledge of the sites are discussed. In both cases, impulsive sources were used in conjunction with air-deployed sonobuoys. Since the measured data was incoherent, only methods consistent with total energy matching were applicable. Comparisons between the different inversion techniques presented at the workshop are discussed. For test cases 4 and 5, a precise metric was unavailable for comparison.     

Benchmarking geoacoustic inversion methods for range-dependent waveguides

Inversion methods have been developed over the past decade to extract information about unknown ocean-bottom environments from acoustic field data. This paper summarizes results from the Office of Naval Research/Space and Naval Warfare Systems Command (SPAWAR) Geoacoustic Inversion Techniques Workshop, which was designed to benchmark present-day inversion methods. The format of the workshop was a blind test to estimate unknown geoacoustic profiles by inversion of synthetic acoustic field data. The fields were calculated using a high-angle parabolic approximation and verified using coupled normal modes for three range-dependent shallow-water test cases: a monotonic slope; a shelf break; and a fault intrusion in the sediment. Geoacoustic profiles were generated to simulate sand, silt, and mud sediments in these environments. Several different approaches for inverting the acoustic field data were presented at the workshop: model-based matched-field methods; perturbation methods; methods using transmission loss data; and methods using horizontal array information. An effective inversion must provide both an estimate of the bottom parameters and a measure of the uncertainty of the estimated values. New methods were presented at the workshop to formalize the measure of uncertainty in the inversion. Comparisons between the different inversions are discussed in terms of a metric-based transmission loss calculated using the inverted profiles. The results demonstrate the effectiveness of present-day inversion techniques and indicate the limits of their capabilities for range-dependent waveguides.     

A hybrid simplex genetic algorithm for estimating geoacousticparameters using matched-field inversion

Matched-fieId inversion (MFI) undertakes to estimate the geometric and geoacoustic parameters in an ocean acoustic scenario by matching acoustic field data recorded at hydrophone array with numerical calculations of the field. The model which provides the best fit to the data is the estimate of the actual experimental scenario. MFI provides a comparatively inexpensive method for estimating ocean bottom parameters over an extensive area. The basic components of the inversion process are a sound propagation model and matching (minimization) algorithm. Since a typical MFI problem requires a large number of computationally intensive sound propagation calculations, both of these components have to be efficient. In this study, a hybrid inversion algorithm which uses a parabolic equation propagation model and combines the downhill simplex algorithm with genetic algorithms is introduced. The algorithm is demonstrated on synthetic range-dependent shallow-water data generated using the parabolic equation propagation model. The performance for estimating the model parameters is compared for realistic signal-to-noise ratios in the synthetic data