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.     

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.     

Geoacoustic Uncertainties From Viscoelastic Inversion of Seabed Reflection Data

This paper applies nonlinear Bayesian inversion to seabed reflection data to estimate viscoelastic parameters of the upper sediments. The inversion provides maximum a posteriori probability (MAP) parameter estimates with uncertainties quantified in terms of marginal probability distributions, variances, and credibility intervals; interparameter relationships are quantified by correlations and joint marginal distributions. The inversion is applied to high-resolution reflectivity data from two sites in the Strait of Sicily. One site is characterized by low-speed sediments, resulting in data with a well-defined angle of intromission; the second is characterized by high-speed sediments, resulting in a critical angle. Data uncertainties are quantified using several approaches, including maximum-likelihood (ML) estimation, treating uncertainties as nuisance parameters in the inversion, and analysis of experimental errors. Statistical tests are applied to the data residuals to validate the assumed uncertainty distributions. Excellent results (i.e., small uncertainties) are obtained for sediment compressional-wave speed, compressional attenuation, and density; shear parameters are less well determined although low shear-wave speeds are indicated. The Bayesian analysis provides a quantitative comparison of inversion results for the two sites in terms of the resolution of specific geoacoustic parameters, and indicates that the geoacoustic information content is significantly higher for intromission data     

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.     

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。     

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.     

Combined Geoacoustic Inversion of Propagation and Reverberation Data

Sonar performance predictions in shallow water are strongly dependent on good knowledge of the geoacoustic and scattering properties of the seabed. One technique to extract information about the bottom is to use a towed source and a towed horizontal array. This towed system has been shown to be applicable for characterizing the bottom properties locally by inversion of the acoustic signals received directly on the towed array at short ranges. The same towed system has also been applied to extract bottom properties from long-range reverberation data providing effective bottom properties over a large area. However, independent geoacoustic inversion of the short-range propagation and long-range reverberation data can introduce low sensitivity and uncertainty in the extracted bottom properties. An attempt to resolve this low sensitivity and ambiguity is made by a simultaneous geoacoustic inversion of short-range propagation and long-range reverberation data with the intention of constraining the possible solutions of the bottom properties.      

Geoacoustic characterization of a range-dependent ocean environment using towed array data

This paper examines geoacoustic inversion over a range-dependent multiple-layer seabed using a towed acoustic source and towed horizontal array. The approach is based on combining the results of a series of short-range, range-independent inversions to form a range-dependent representation of the environment. The data were collected in the Strait of Sicily during the MAPEX 2000 experiment. Issues such as the resolvability of multilayer structure and the sensitivity of various geoacoustic parameters are investigated by inversion of simulated data and by comparison of the MAPEX 2000 inversion results to a high-resolution seismic profile and to sediment core measurements. It appears that two, and in some cases possibly three, sediment layers can be resolved.     

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。     

Performance comparison between vertical and horizontal arrays for geoacoustic inversion

Most of the research on model-based geoacoustic inversion techniques has concentrated on data collected using moored vertical receiver arrays. However, there are many advantages to considering geoacoustic inversion using a towed horizontal array. Towed arrays are easily deployed from a moving platform; this mobility makes them well suited for surveying large areas for sea-bed properties. Further, if a model-based geoacoustic inversion scheme uses both a towed source and array, the separation between the two can be kept short, which reduces the requirement for range-dependent modeling. Range-independent modeling is used for inverting all the horizontal array data considered in this paper. Using the Inversion Techniques Workshop Benchmark Test Cases, the performance of a horizontal (simulated towed) and vertical arrays are compared and found to be very similar. However, it will be shown that, for Benchmark Test Case 3, where the bathymetry is flat and a hidden bottom intrusion exists, a towed horizontal array is ideal for determining the range-dependent sea-bed properties. The practical advantages of using a towed array are clear and the purpose of this paper is to show that the performance is similar (and in some cases better) than using moored vertical arrays.     

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。     

Geoacoustic seafloor exploration with a towed array in a shallowwater area of the Strait of Sicily

Acoustic propagation in shallow water is greatly dependent on the geoacoustic properties of the seabottom. This paper exploits this dependence for estimating geoacoustic sediment properties from the bottom acoustic returns of known signals received on a hydrophone line array. There are two major issues in this approach: one is the feasibility of acoustic inversion with a limited aperture line array, the other is related to the knowledge of the geometry of the experimental configuration. To test the feasibility of this approach, a 40-hydrophone-4-m spaced towed array together with a low-frequency acoustic source, was operated at a shallow water site in the Strait of Sicily. In order to estimate the array deformation in real time, it has been equipped with a set of nonacoustic positioning sensors (compasses, tilt-meters, pressure gauges). The acoustic data were inverted using two complementary approaches: a genetic algorithm (GA) like approach and a radial basis functions (RBF) inversion scheme. More traditional methods, based on core sampling, seismic survey and geophone data, together with Hamilton's regression curves, have also been employed on the same tracks, in order to provide a ground truth reference environment. The results of the experiment, can be summarized as follows: 1) the towed array movement is not negligible for the application considered and the use of positioning sensors are essential for a proper acoustic inversion, 2) the inversion with GA and RBF are in good qualitative agreement with the ground truth model, and 3) the GA scheme tends to have better stability properties. On the other hand, repeated in version of successive field measurements requires much less computational effort with RBF     

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。     

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.     

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.     

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.     

Geoacoustic inversion using a rotated coordinate system and simulated annealing

An efficient method for geoacoustic inversions in a range-dependent ocean waveguide is implemented and tested with synthetic data. This method combines a simulated annealing search with an optimal coordinate rotation that increases the efficiency of navigating parameter landscapes for which parameter coupling is important. The coordinate rotation associated with the parameter couplings also provides information about which parameters are resolvable for a particular inversion frequency and array geometry. Using this information, results from several single-frequency inversions can be combined to obtain an estimate for the sediment parameters.     

Estimates of geoacoustic model parameters from inversions of horizontal and vertical line array data

This paper describes results from geoacoustic inversion of low-frequency acoustic data recorded at a receiving array divided into two sections, a sparse bottom laid horizontal array (HLA) and a vertical array (VLA) deployed in shallow water. The data are from an experiment conducted by the Norwegian Defence Research Establishment (FFI) in the Barents Sea, using broadband explosives (shot) sources. A two-layer range-independent geoacoustic model, consistent with seismic profiles from the area, described the environment. Inversion for geoacoustic model parameters was carried out using a fast implementation of the hybrid adaptive simplex simulated annealing (ASSA) inversion algorithm, with replica fields computed by the ORCA normal mode code. Low-frequency (40-128 Hz) data from six shot sources at ranges 3-9 km from the array were considered. Estimates of sediment and substrate p-wave velocities and sediment thickness were found to be consistent between independent inversions of data from the two sections of the array.     

Application of an improved self-starter to geoacoustic inversion

The self-starter is improved using the operator of the split-step Pade solution. In addition to providing greater stability and being applicable closer to the source, the improved self-starter is an efficient forward model for geoacoustic inversion. It is necessary to solve only O(10) tridiagonal systems of equations to obtain the acoustic field on a vertical array located O(10) wavelengths from a source. This experimental configuration is effective for geoacoustic inverse problems involving unknown parameters deep in the ocean bottom. For problems involving depth-dependent acoustic parameters, the improved self-starter can be used to solve nonlinear inverse problems involving O(10) unknown sediment parameters in less than a minute on the current generation of workstations     

Time-domain geoacoustic inversion of high-frequency chirp signal from a simple towed system

An inversion method using a towed system consisting of a source and two receivers is presented. High-frequency chirp signals that have been emitted from the source are received after multiple penetrations and reflections from the shallow water sub-bottom structure and are processed for geoacoustical parameter estimation. The data are processed such that a good resolution and robustness is achieved via matched filtering, which requires information about the source signal. The inversion is formulated as an optimization problem, which maximizes the cost function defined as a normalized correlation between the measured and modeled signals directly in the time domain. The very fast simulated reannealing optimization method is applied to the global search problem. The modeled time signal is obtained using a ray approach. An experiment was carried out in the Mediterranean Sea using a towed source and receiver system. The inversion method is applied to the experimental data and results are found to be consistent with previous frequency-domain analyses using measurements from a towed horizontal array of receivers and measurements on a vertical array.