Model-based identification: an adaptive approach to ocean-acousticprocessing

A model-based approach is developed to solve an adaptive ocean-acoustic signal-processing problem. Model-based signal processing is a well-defined methodology enabling the inclusion of propagation models, measurement models, and noise models into sophisticated processing algorithms. Here, we investigate the design of a so-called model-based identifier (MBID) for a general nonlinear state-space structure and apply it to a shallow water ocean-acoustic problem characterized by the normal-mode model. In this problem, we assume that the structure of the model is known and we show how this parameter-adaptive processor can be configured to jointly estimate both the modal functions and the horizontal wave numbers directly from the measured pressure-field and sound speed. We first design the model-based identifier using a model developed from a shallow-water ocean experiment and then apply it to a corresponding set of experimental data demonstrating the feasibility of this approach. It is also shown that one of the benefits of this adaptive approach is a solution to the so-called “mismatch” problem in matched-field processing (MFP)     

Spatial diversity equalization applied to underwater communications

Underwater acoustic digital communication is difficult because of the nature of the fading multipath channels. Digital signal processing, such as adaptive equalization, is known to greatly improve the communication data rate by limiting intersymbol interference (ISI). However, existing underwater acoustic equalization studies are limited to single-channel techniques, and spatial diversity processing is limited to selection or combining. In this paper, we design minimum mean-square error (MMSE) equalizers jointly among all spatial diversity channels. We call this spatial diversity equalization (SDE). Results are based on a very sparse vertical array in a midrange underwater acoustic channel. We study the effect of element number and placement, the length of the equalization filters, and linear feedforward versus nonlinear decision feedback algorithms. A suboptimum equalizer combiner (EC) is studied to alleviate the computational intensity of JCE. We first design the system for a known acoustic channel; later, some results are verified using adaptive algorithms. Results are presented both in terms of the mean-square error (MSE) and the probability of a symbol error. The latter is important as it is the ultimate interest for a digital communication system. We found that system performance improves rapidly with an increase in the number of spatial channels     

Deep-water acoustic coherence at long ranges: theoreticalprediction and effects on large-array signal processing

This paper presents results of combined consideration of sound coherence and array signal processing in long-range deep-water environments. Theoretical evaluation of the acoustic signal mutual coherence function (MCF) of space for a given sound-speed profile and particular scattering mechanism is provided. The predictions of the MCF are employed as input data to investigate the coherence-induced effects on the horizontal and vertical array gains associated with linear and quadratic beamformers with emphasis on the optimal ones. A method of the radiation transport equation is developed to calculate the MCF of the multimode signal under the assumption that internal waves or surface wind waves are the main source of long-range acoustic fluctuations in a deep-water channel. Basic formulations of the array weight vectors and small signal deflection are then exploited to examine optimal linear and quadratic processors in comparison with plane-wave beamformers. For vertical arrays, particular attention is paid also to evaluation of the ambient modal noise factor. The numerical simulations are carried out for range-independent environments from the Northwest Pacific for a sound frequency of 250 Hz and distances up to 1000 km. It was shown distinctly that both signal coherence degradation and modal noise affect large-array gain, and these effects are substantially dependent on the processing technique used. Rough surface sound scattering was determined to cause the most significant effects     

Single hydrophone source localization

The method presented in this paper assumes that the received signal is a linear combination of delayed and attenuated uncorrelated replicas of the source emitted waveform. The set of delays and attenuations, together with the channel environmental conditions, provide sufficient information for determining the source location. If the transmission channel is assumed known, the source location can be estimated by matching the data with the acoustic field predicted by the model conditioned on the estimated delay set. This paper presents alternative techniques that do not directly attempt to estimate time delays from the data but, instead, estimate the subspace spanned by the delayed source signal paths. Source Localization is then done using a family of measures of the distance between that subspace and the subspace spanned by the replicas provided by the model. Results obtained on the INTIMATE'96 data set, in a shallow-water acoustic channel off the coast of Portugal, show that a sound source emitting a 300-800-Hz LFM sweep could effectively be localized in range or depth over an entire day     

Model-based processing for a large aperture array

A model-based approach to solve a deep water ocean acoustic signal processing problem based on a state-space representation of the normal-mode propagation model is developed. The design of a model-based processor (MBP) for signal enhancement employing an array consisting of a large number of sensors for a deep ocean surveillance operation is discussed. The processor provides enhanced estimates of the measured pressure-field, modes, and residual (innovations) sequence indicating the performance or adequacy of the propagation model relative to the data. It is shown that due to the structure of the normal-mode model the state-space propagator is not only feasible for this large scale problem, but in fact, can be implemented by a set of decoupled parallel second-order processors, implying a real-time capability. In the paper we discuss the design and application of the processor to a realistic set of simulated pressure-field data developed from a set of experiments and sound speed parameters     

Channel Modeling and Threshold Signal Processing in Underwater Acoustics: An Analytical Overview

An overview of underwater acoustic channel modeling and threshold signal processing is presented, which emphasizes the inhomogeneous, random, and non-Ganssian nature of the generalized channel, combined with appropriate weak-signal detection and estimation. Principal attention is given to the formal structuring of the scattered and ambient acoustic noise fields, as well as that of the desired signal, including both fading and Doppler "smear" phenomena. The role of general receiving arrays is noted, as well as their impact on spatial and temporal signal processing and beam forming, as indicated by various performance measures in detection and estimation. The emphasis here is on limiting optimum threshold systems, with some attention to suboptimum cases. Specific first-order probability density functions (pdf's) for the non-Ganssian components of typical underwater acoustic noise environments are included along with their field covariances. Several examples incorporating these pdf's are given, to illustrate the applications and general methods involved. The fundamental role of the detector structure in determining the associated optimum estimators is noted: the estimators arc specific linear or nonlinear functionals of the original optimum detector algorithm, depending on the criterion (i.e., minimization of the chosen error or cost function) selected. Results for both coherent and incoherent modes of reception are presented, reflecting the fact that frequently signal epoch is not known initially at the receiver. To supplement the general discussion, a selected list of references is included, to provide direct access to specific detailed problems, techniques, and results, for which the present paper is only a guide.     

Real time time-frequency active sonar processing: a SIMD approach

A paradigm for massively parallel processing of matched filters, replica correlators, ambiguity functions, and time-frequency distributions is presented, using a SIMD (single instruction stream, multiple data stream) programming methodology. It is shown that active sonar detection algorithms, as implemented by frequency domain processing, can be a natural match to a SIMD methodology, meeting the extensive computational needs of enhanced active sonar systems. The decomposition process is presented, and examples are given of the output of the computer program CMASP (Connection Machine Ambiguity Surface Processor). CMASP can provide real-time simultaneous multiple-beam, Doppler, and waveform replica correlations. Synthetic data are processed, and the corresponding CMASP outputs are displayed as three-dimensional ambiguity surfaces on networked graphic workstations. Because of efficient problem decomposition, other time-frequency processing can be exploited. Specifically, real-time instantaneous-like time-frequency distributions have been realized in which the data set is presented and processed as time-varying spectral representations     

Forward Scattering Observation With Partially Coherent Spatial Processing of Vertical Array Signals in Shallow Water

In this paper, we address the problem of detecting an inhomogeneity in shallow water by observing changes in the acoustic field as the inhomogeneity passes between an acoustic source and vertical line array of receivers. A signal processing scheme is developed to detect the perturbed field in the presence of the much stronger primary source signal, and to estimate such parameters as the time when the inhomogeneity crosses the source-receiver path, its velocity, and its size. The effectiveness of incoherent, coherent, and partially coherent spatial processing of the array signals is evaluated using models and data obtained from experiments in a lake. The effect of different bottom types is also considered, and it is shown that partially coherent processing can have a significant advantage depending on the bottom type. Estimates of the minimum input signal-to-noise ratios (SNRs) for which the diffracted signal can be observed are presented.     

海底沉积物声学特征定量分析及其智能分类研究

海底底质特性描述及分类是当今浅海声学的研究热点,海底沉积物的物理结构特性与其声学响应特征密切相关。在分析海底沉积物声传播特性的基础上,应用现代计算机信号分析技术手段,对海底沉积物声学响应波形提取了4个特征参数:声速、波幅指数、波形关联维分形指数和声波频谱的频率矩。以这4个特征参数作为输入向量,海底沉积物的结构类型作为输出向量,建立径向基概率神经网络模型。研究表明建立的神经网络模型具有较强的海底沉积物分类预报能力。     

Low-bit-rate coding of underwater video using wavelet-basedcompression algorithms

Recent advances in autonomous underwater vehicle (AUV) and underwater communication technology have promoted a surge of research activity within the area of signal and information processing. A new application is proposed herein for capturing and processing underwater video onboard an untethered AUV, then transmitting it to a remote platform using acoustic telemetry. Since video communication requires a considerably larger bandwidth than that provided by an underwater acoustic channel, the data must be massively compressed prior to transmission from the AUV. Past research has shown that the low contrast and low-detailed nature of underwater imagery allows for low-bit-rate coding of the data by wavelet-based image-coding algorithms. In this work, these findings have been extended to the design of a wavelet-based hybrid video encoder which employs entropy-constrained vector quantization (ECVQ) with overlapped block-based motion compensation. The ECVQ codebooks were designed from a statistical source model which describes the distribution of high subband wavelet coefficients in both intraframe and prediction error images. Results indicate that good visual quality can be achieved for very low bit-rate coding of underwater video with our algorithm     

Acoustic density measurements of consolidating cohesive sediment beds by means of a non-intrusive “Micro-Chirp” acoustic system

A non-intrusive “Micro-Chirp” acoustic system and a signal-processing protocol have been developed to estimate the bulk density of consolidating cohesive sediment beds. Using high-frequency (300–700 kHz) Chirp acoustic waves, laboratory measurements were conducted with clay–water mixtures. Because acoustic echo strength is proportional to variations in acoustic impedance, and the speed of sound in the clay bed hardly changed during consolidation, the bulk density could be successfully estimated without disturbing the sediment bed. Based on acoustic signal analysis, this study demonstrates that the reflection coefficient and bulk density at the water–sediment interface increase with consolidation time, and that a single speed of sound value can be used for practical bulk density estimation in muddy environments.     

三维海洋溢油预测模型的建立(英文)

提出一个海洋溢油三维物理归宿和输运的动力学综合模型。该模型包含了一系列的数学公式来描述对流、湍扩散、表面扩展、铅直扩散、乳化和蒸发过程。每一公式的建立是独立的并且与相关过程、环境和其它参数相联系。该模型需要输入流场作为输运的媒介 ,这可从感兴趣区域的三维潮和风驱动的流体动力学模型获得。模型用来预测和后报溢油在海洋环境中的归宿和输移 ,可为溢油应急反应和环境影响评价服务。     

A distributed microprocessor architecture for fixed and mobile acoustic array adaptive beam forming

This paper presents a state-of-the-art approach to an important sonar signal-processing problem, A theoretical foundation for source oriented beam forming (SOBF) is presented. A distributed processing element is introduced, discussed, and offered as one solution to the at-sea platform implementation of high-powered digital signal processing such as SOBF. While many of the details of the implementation are beyond the scope or intent of this paper, they may be found in the references (those references not in the open literature are obtainable from the authors).     

Remote sensing of ocean sound speed profiles by a perceptron neuralnetwork

A method is developed to estimate ocean sound speed profiles through synthesis of remotely measured environmental data and historical statistics of sound speed obtained at a remotely sensed location. Sound speed profiles are represented by an expansion of empirical orthogonal functions (EOF) of the historical sound speed variation, while the remotely sensed environmental data provide real-time information to determine the expansion coefficients. Environmental inputs are limited to sea surface temperature available from satellite infrared sensors, acoustic time-of-flight and ocean bottom temperature measurable from bottom mounted acoustic and thermal transducers. A multilayer perceptron neural network is implemented to learn the functional transformation from the measured environmental input to the desired EOF coefficient output on a set of representative sound speed profiles. Sea surface temperature, time-of-year, and time-of-flight from the acoustic multipath that maximally samples the vertical sound speed are found to be the dominant inputs. The trained network is computationally efficient and produces estimates for untrained environmental inputs with a mean error of 1.1-4.4 m/s     

Extension of synthetic aperture radar (SAR) technique to undersea applications

This paper presents results on the extension of synthetic-aperture radar (SAR) technique to underwater mapping applications. Due to the modest propagation speed of acoustic waves in water, the areal-mapping rate is found to be limited. A number of approaches are discussed in the paper which have the potential of significantly increasing the mapping rate. The map resolutions, both in azimuth and range, are derived for a synthetic array system employing multiple elements. The digital processing requirements, such as the complex multiplication rate and memory size are determined. It was found that the digital signal-processing requirements for many viable mapping systems are within the capability of existing processing hardware.     

水声环境资料质量检核评估标准规范研究

为规范水声环境资料质量检核评估工作,开展了水声环境资料质量检核评估标准规范研究,参照水声环境数据后期处理一般程序,梳理分析了原始数据、处理算法、模型运用及处理流程等数据质量误差来源;结合标准化水声环境资料处理程序及成果形式,研究了数据及数据处理全流程检核评估方法,给出数据文件、处理代码及配套文档资料应包含的内容及检查方法;研判了数据质量检核评估要求,给出三级验收制度、检核评估形式及提交的资料清单要求,对开展水声环境资料验收汇交规程及相关标准规范的制定、修订工作,具有较强的参考价值。     

Recent advances in high-speed underwater acoustic communications

In recent years, underwater acoustic (UWA) communications have received much attention as their applications have begun to shift from military toward commercial. Digital communications through UWA channels differ substantially from those in other media, such as radio channels, due to severe signal degradations caused by multipath propagation and high temporal and spatial variability of the channel conditions. The design of underwater acoustic communication systems has until recently relied on the use of noncoherent modulation techniques. However, to achieve high data rates on the severely band-limited UWA channels, bandwidth-efficient modulation techniques must be considered, together with array processing for exploitation of spatial multipath diversity. The new generation of underwater communication systems, employing phase-coherent modulation techniques, has a potential of achieving at least an order of magnitude increase in data throughput. The emerging communication scenario in which the modern underwater acoustic systems mill operate is that of an underwater network consisting of stationary and mobile nodes. Current research focuses on the development of efficient signal processing algorithms, multiuser communications in the presence of interference, and design of efficient modulation and coding schemes. This paper presents a review of recent results and research problems in high-speed underwater acoustic communications, focusing on the bandwidth-efficient phase-coherent methods. Experimental results are included to illustrate the state-of-the-art coherent detection of digital signals transmitted at 30 and 40 kb/s through a rapidly varying one-mile shallow water channel     

A piecewise matched-field tracking algorithm

Matched-field tracking (MFT) algorithms have been successfully applied to both simulated and measured data to determine the most likely positions of a sound source that is localized ambiguously by a matched-field processing (MFP) system. They have been used to track sources moving linearly or on a circular path at constant speed and heading. The input to the trackers is a set of ambiguity surfaces, contiguous in time, generated by MFP. These algorithms assume that the track start and end times are known a priori; this restriction is removed in the piecewise MFT algorithm (PTA). The PTA was applied to narrow-band measured data collected during the PACIFIC SHELF 93 trial to successfully identify the significant source track segments     

Ocean acoustic field matching: normal mode filtering andnon-Gaussian sources

Two qualitative results concerning statistical sonar signal processing and acoustic field matching are obtained. First, normal-mode field predictions are integrated with statistical signature analysis by constructing a boundary-value problem in the acoustic waveguide. From this construction it is found that the normal-mode filter is the unique acoustic preprocessor which does not confound deterministic waveguide correlation structure with stochastic source covariance structure. Second, the origin of deterministic, Gaussian, and non-Gaussian source signatures is investigated by associating physical parameters with the classical Lindeberg central limit conditions. From construction it is found that there are important objects that are not adequately represented either by infinitesimal points or by infinite surfaces. If receiver resolution is inadequate to resolve source complexity, these objects will exhibit a non-Gaussian acoustic signature via an entirely linear progression from internal excitation, to source radiation, through waveguide propagation, and finally to reception