An overview of matched field methods in ocean acoustics

A short historical overview of matched-field processing (MFP) is followed by background material in both ocean acoustics and array processing needed for MFP. Specific algorithms involving both quadratic and adaptive methods are then introduced. The results of mismatch studies and several algorithms designed to be relatively robust against mismatch are discussed. The use of simulated MFP for range, depth and bearing location is examined, using data from a towed array that has been tilted to produce an effective vertical aperture. Several experiments using MFP are reviewed. One successfully demonstrated MFP at megameter ranges; this has important consequences for experiments in global tomography. Some unique applications of MFP, including how it can exploit ocean inhomogeneities and make tomographic measurements of environmental parameters, are considered     

Matched-field processing in a range-dependent shallow waterenvironment in the Northeast Pacific Ocean

This paper describes matched-field processing (MFP) of data collected in shallow water off the western coast of Vancouver Island in the Northeast Pacific Ocean. The data were collected from a vertical line array (VLA) as part of the PACIFIC SHELF trial carried out on the continental shelf and slope during September 1993, sensors in the 16-element VLA were evenly spaced at depths between 90 and 315 m, while the sound source was towed along radial paths or arcs. In this paper, we present results of the analysis of data from a continuous wave (CW) source which was towed downslope at a depth of 30 m in water from 150 to 375 m deep, in order to model the range-dependence of the acoustic propagation efficiently, the replica fields were calculated using the adiabatic normal mode approximation. This approximation was considered appropriate for the bottom slopes of the environment. Using sparse bathymetric data, a water sound speed profile and estimates of bottom properties, MFP correlations on individual ambiguity surfaces were found to be greater than 0.9 for the strongest signals. On account of environmental mismatch, the source position could not be determined unambiguously from most of the ambiguity surfaces even at high signal-to-noise ratios. Nevertheless, when an efficient linear tracker was applied to the ambiguity surfaces to find tracks, the source track was recovered at both low and high signal-to-noise ratios, this tracker performs the analysis at a constant depth and reports the track with the highest estimated track signal-to-noise ratio     

VLF source localization with a freely drifting acoustic sensorarray

The source localization and tracking capability of the freely drifting Swallow float volumetric array is demonstrated with the matched-field processing (MFP) technique using the 14-Hz CW data collected during a 1989 float experiment conducted in the northeast Pacific. Initial MFP of the experimental data revealed difficulties in estimating the source depth and range while the source azimuth estimate was quite successful. The main cause of the MFP performance degradation was incomplete knowledge of the environment. An environment adaptation technique using a global optimization algorithm was developed to alleviate the environmental mismatch problem, allowing the ocean-acoustic environment to be adapted to the acoustic data in a matched-field sense. Using the adapted environment, the 14-Hz source was successfully localized and tracked in azimuth and range within a region of interest using the MFP technique at a later time interval. Two types of environmental parameters were considered, i.e., sound speed and modal wave number. While both approaches yield similar results, the modal wave number adaptation implementation is more computationally efficient     

A Portable Matched-Field Processing System Using Passive Acoustic Time Synchronization

A portable matched-field processing (MFP) system for tracking marine mammals is presented, constructed by attaching a set of autonomous flash-memory acoustic recorders to a rope to form a four-element vertical array, or "insta-array." The acoustic data are initially time-synchronized by performing a matched-field global inversion using acoustic data from an opportunistic source, and then by exploiting the spatial coherence of the ocean ambient noise background to measure and correct for the relative clock drift between the autonomous recorders. The technique is illustrated by using humpback whale song collected off the eastern Australian coast to synchronize the array, which is then used to track the dive profile of the whale using MFP methods. The ability to deploy autonomous instruments into arbitrary "insta-array" geometries with conventional fishing gear may permit nonintrusive array measurements in regions currently too isolated, expensive, or environmentally hostile for standard acoustic equipment     

Using matched-field processing to estimate shallow-water bottomproperties from shot data taken in the Mediterranean Sea

It is extremely difficult to determine shallow ocean bottom properties (such as sediment layer thicknesses, densities, and sound speeds). However, when acoustic propagation is affected by such environmental parameters, it becomes possible to use acoustic energy as a probe to estimate them. Matched-field processing (MFP) which relies on both field amplitude and phase can be used as a basis for the inversion of experimental data to estimate bottom properties. Recent inversion efforts applied to a data set collected in October 1993 in the Mediterranean Sea north of Elba produce major improvements in MFP power, i.e., in matching the measured field by means of a model using environmental parameters as inputs, even using the high-resolution minimum variance (MV) processor that is notoriously sensitive and usually results in very low values. The inversion method applied to this data set estimates water depth, sediment thickness, density, and a linear sound-speed profile for the first layer, density and a linear sound-speed profile for a second layer, constant sound speed for the underlying half space, array depth, and source range and depth. When the inversion technique allows for the array deformations in range as additional parameters (to be estimated within fractions of a wavelength, e.g., 0.1 m), the MFP MV peak value for the Med data at 100 Hz can increase from 0.48 (using improved estimates of environmental parameters and assuming a vertical line array) to 0.68 (using improved estimates of environmental parameters PLUS improved phone coordinates). The ideal maximum value would be 1.00 (which is achieved for the less sensitive Linear processor). However, many questions remain concerning the reliability of these inversion results and of inversion methods in general     

Estimation and detection issues in matched-field processing

A conceptual framework in which the model-based, space-time acoustic signal processing procedure known as matched field processing (MFP) can be handled in a consistent manner is established. A framework for strong-signal MFP based on standard statistical estimation theory, in which MFP is regarded as essentially an estimation problem in the strong-signal regime, is developed. In the weak-signal case, the necessary requirement of detection dictates that MFP then be considered a joint detection-estimation task. It is demonstrated that, generally, MFP is essentially a space-time processing problem rather than simply an array processing (spatial processing only) procedure. An overview of the processing schemes used to date in MFP is given, showing how these methods relate to the optimal space-time structure. Weak-signal detection and estimation scenarios relevant to MFP are then noted. Present methods for dealing with the inherent instability of MFP algorithms (mismatch) are discussed. The current status of MFP is summarized, and recommendations for future research are made     

Fast matched field processing

It is shown how the computational burden of source localization by matched field processing (MFP) can be significantly reduced (20 to 30 times) by expressing the correlation in terms of a discrete Fourier transform and using the fast Fourier transform (FFT) algorithm. The price paid to achieve increased speed is in the form of quantization phase errors. It is shown through analysis and computer simulation that the quantization errors reduce the source peak height, depending upon the size of DFT. The proposed fast MFP works for range localization only. However, the depth estimation is possible by repeated application of the above algorithm for different depths     

Matched field inversion for geoacoustic model parameters usingadaptive simulated annealing

A method is described for the estimation of geoacoustic model parameters by the inversion of acoustic field data using a nonlinear optimization procedure based on simulated annealing. The cost function used by the algorithm is the Bartlett matched-field processor (MFP), which related the measured acoustic field with replica fields calculated by the SAFARI fast field program. Model parameters are perturbed randomly, and the algorithm searches the multidimensional parameter space of geoacoustic models to determine the parameter set that optimizes the output of the MFP. Convergence is driven by adaptively guiding the search to regions of the parameter space associated with above-average values of the MFP. The performance of the algorithm is demonstrated for a vertical line array in a shallow water enviornment where the bottom consists of homogeneous elastic solid layers. Simulated data are used to determine the limits on estimation performance due to error in experimental geometry and to noise contamination. The results indicate that reasonable estimates are obtained for moderate conditions of noise and uncertainty in experimental geometry     

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)     

Experimental matched-field localization results using a short vertical array and mid-frequency signals in shallow water

Traditionally, matched-field processing (MFP) has been used to localize low-frequency sources (e.g., <300 Hz) from their acoustic signals received on long vertical arrays. However, some sources emit acoustic signals of much higher frequency. Applying MFP to signals in the mid-frequency range (e.g., 1-4 kHz) is a very challenging problem because MFP's sensitivity to environmental parameter mismatch becomes more severe with increasing frequency. Robust MFP techniques are required to process signals in the mid-frequency range. As a practical issue, short vertical arrays are more convenient to work with than are long vertical arrays; they are easier to deploy and are less prone to large amounts of deformation. However, short vertical arrays undersample the water column, which can result in severely degraded MFP performance. In this paper, we present experimental data results for this nonconventional paradigm. Using the environmentally robust broad-band L/sub /spl infin//-norm estimator, MFP results are given using shallow-water experimental data. This data consisted of broad-band signals in the 3-4-kHz band collected on an eight-element 2.13-m vertical array. These results serve to demonstrate that good localization performance can be attained for this difficult problem. Guidelines on the appropriate use of ray and normal-mode propagation models are also presented.     

Track Parameter Estimation from Multipath Delay Information

It is desired to track the location of an underwater acoustic source with range difference measurements from a stationary passive array. Many times, the array has only one or two sensors, and the multipath and intersensor range difference measurements are insufficient to localize and track a source moving along an arbitrary path [1]. Here, we propose to track sources with one- or two-sensur stationary passive arrays by making the simplifying assumption that the source's path can be described by a small set of so-called track parameters. Range difference information can then be used to estimate the track parameter set rather than the source location as a function of time. In this paper, we choose the track parameters to specify a straight-line constant-velocity constant-depth path. Cramer-Rao bounds are presented for estimating these track parameters from the time history of multipath and intersensor range difference measurements. It is shown that this track parameter set cannot be accurately estimated from the time history of a single multipath range difference without side information (an independent velocity estimate, for instance), although multipath and intersensor range difference measurements from a two-sensor array are generally sufficient to estimate the track parameter set. Computationally efficient techniques are presented which estimate track parameters from range difference measurements taken from one- and two-sensor arrays. Monte-Carlo simulations are presented which show that these techniques have sample mean-square error approximately equal to the Cramer-Rao bound when a single multipath range difference and an independent velocity estimate are available. The sample mean-square error is shown to be in the range of two to ten times the corresponding Cramer-Rao bounds when these techniques are applied to two-sensor range difference data.     

Adaptive beamforming of a towed array during a turn

During maneuvering, towed array beamforming degrades if a straight array is assumed. This is especially true for high-resolution adaptive beamforming. It is experimentally demonstrated that adaptive beamforming is feasible on a turning array, provided that array shape is estimated. The array shape can be inferred solely from the coordinates of the tow vessel's Global Positioning System (GPS) without any instrumentation in the array. Based on estimated array shape from the GPS, both the conventional beamformer and the white noise constrained (WNC) adaptive beamformer are shown to track the source well during a turn. When calculating the weight vector in the WNC approach, a matrix inversion of the cross-spectral density matrix is involved. This matrix inversion can be stabilized by averaging the cross-spectral density matrix over neighboring frequencies. The proposed algorithms have been tested on real data with the tow-vessel making 45/spl deg/ turns with a 500-m curvature radius. While turning, the improvement in performance over the assumption of a straight array geometry was up to 5 dB for the conventional beamformer and considerably larger for the WNC adaptive beamformer.     

Interrelations between matched-field processing and airborne MTIradar

In matched field processing (MFP) the spatial characteristics of a dispersive wave field are exploited to estimate certain parameters of the acoustic field, such as source location or characteristics of the acoustic channel including environmental parameters. In airborne MTI (AMTI) radar, interfering echoes (clutter) are Doppler colored due to the platform motion. Optimum clutter suppression requires space-time or space-frequency processing. Some thoughts concerning cross-fertilization between these two areas are put forward. In particular, the idea of space-time MFP is stressed. A processor for space-time power estimation is proposed     

Acoustic tracking of a freely drifting sonobuoy field: experimental results

This paper describes a regularized acoustic inversion algorithm for tracking individual elements of a freely drifting sonobuoy field using measured acoustic arrival times from a series of impulsive sources. The acoustic experiment involved 11 sonobuoys distributed over an 8/spl times/6-km field, with a total of six sources deployed over 72 min. The inversion solves for an independent track for each sonobuoy (parameterized by the sonobuoy positions at the time of each source transmission), as well as for the source positions and transmission instants. Although this is a strongly under-determined problem, meaningful solutions are obtained by incorporating a priori information consisting of prior estimates (with uncertainties) for the source positions and initial sonobuoy positions and a physical model for sonobuoy motion along preferentially smooth tracks. The inversion results indicate that the sonobuoys move approximately 260-700 m during the source-deployment period. Closely spaced sonobuoys move along similar tracks; however, there is considerable variability in track directions over the entire field. Positioning uncertainties in horizontal coordinates are estimated using a Monte Carlo appraisal procedure to be approximately 100 m in an absolute sense and 65 m in a relative sense. A sensitivity study indicates that the uncertainties of the a priori position estimates are the limiting factor for track accuracy, rather than data uncertainties or source configuration.     

Robust Range-Only Beacon Localization

In this paper, we present a system capable of simultaneously estimating the position of an autonomous underwater vehicle (AUV) and the positions of stationary range-only beacons. Notably, our system does not require beacon positions a priori, and our system performs well even when range measurements are severely degraded by noise and outliers. We present a powerful outlier rejection method that can identify groups of range measurements that are consistent with each other, and a method for initializing beacon positions in an extended Kalman filter (EKF). We have successfully applied our algorithms to real-world data and have demonstrated a simultaneous localization and mapping (SLAM) system whose navigation performance is comparable to that of systems that assume known beacon locations     

基于Prophet算法的海南近海波浪长时段时序分析与预测

近年来,以大数据为基础的人工智能算法逐步兴起并被用于海洋波浪短期预测.本文采用2015-2019年海南近海逐时波浪实测时序数据,基于Prophet算法建立了海南近海波浪长时段时序预测模型,分析了2015-2019年海南近海波浪日、月、年变化特性,并对海南近海2020年波浪变化过程进行了预测.结果显示,Prophet算法...     

A Comparison of Sea Surface Fluxes over Southern Indian Ocean Cruise Expedition Observation and NCEP Reanalysis

Surface layer atmospheric and ocean observations have been collected along the cruise track from a special scientific expedition to Antarctica. Bulk estimates of surface momentum flux, sensible heat flux and latent heat flux have been computed applying bulk algorithms from the data collected along cruise track during the time period January 27 to March 31, 2006, and compared the results with National Centre for Environmental Prediction (NCEP) reanalysis. Underestimation of surface momentum flux in roaring forties (40°S–50°S) area of Indian Ocean is seen from NCEP reanalysis. Systemic differences in sensible and latent heat fluxes between observed and NCEP reanalysis have been found. Along the cruise track, the average sensible (latent) heat flux was 9.45 Wm^?2 (67.46 Wm^?2) and 3.75 Wm^?2 (64.45 Wm^?2) from the direct measurement and NCEP reanalysis, respectively. The NCEP reanalysis is being widely used in numerical modeling studies, and the discrepancies shown in the NCEP reanalysis in present study will be of immense use to the modeling community of the Indian Ocean in general and Southern Indian Ocean in particular.     

Ray Theory Application in Long Baseline System

The long baseline (LBL) system is widely used to locate and track autonomous underwater vehicles (AUV) through acoustic communication.Three important issues are presented here in LBL system application with AUV.Those issues which regard the normal acoustic communication between LBL system and AUV are the depth of towed array,the length of beacon cable,and the effective area of the AUV.The first issue is the key of the LBL system,which ensures the normal communication between towed array and beacons.The second issue which impacts the normal communication from the AUV to beacons in available range should be considered after the first one has been settled.Then the last issue determines the safe work area of the AUV.The ordinary differential equations (ODE) algorithm of ray is deduced from Snell′s law.The ODE algorithm is applied to obtain sound rays from sound source to receiver.These problems are solved by the judgment that whether rays pinging from a sound source arrives at a receiver.The sea trial shows that these methods have much validity and practicality.     

Inversion in shallow-water using the WKB modal condition

In this paper, we propose an efficient scheme for extracting the complex bottom reflection coefficient (phase and amplitude) in a shallow water waveguide by using the WKB modal condition. The input data are the measured modal wavenumber (k_m) and the modal attenuation (β_m). The main advantages of this scheme are: 1) it is efficient, because there are no replica calculations as in the conventional matched field processing (MFP) scheme, 2) the inverted error induced by the “noise” of the contaminated data can be estimated analytically, and 3) the impact of the environmental (SSP) mismatch can also be estimated analytically. Numerical simulations illustrate that the proposed scheme works well in different scenarios of shallow water waveguides     

A range-dependent echo-association algorithm and its application insplit-beam sonar tracking of migratory salmon in the Fraser Riverwatershed

Fish sonars have long been used to survey and monitor migratory salmon in rivers and at sea. However, research has been lacking in the development of algorithms to extract fish tracks from data collected in a riverine or oceanic environment. Current fish trackers, based on a pulse-to-pulse tracking method, only work well under ideal conditions when targets are well separated and the signal-to-noise ratio is high. Fisheries biologists often have to identify fish traces visually from raw echograms. This approach is both labor-intensive and time-consuming, limiting the usefulness of hydroacoustic techniques for fisheries management. This paper presents a fish-tracking algorithm which sorts randomly distributed echoes into coherent fish traces. Fish counts obtained with the algorithm compare well with visual counts at two quite different sites in the Fraser River watershed. The key features of the algorithm are: (1) the linking mechanisms among sequential fish echoes are range-dependent; (2) the growth echo for a developing track depends not only on its space-time relation with the previous track echo (the pulse-to-pulse statistics) but also on its relation to the entire track being constructed; (3) there are a total of only five echo-association criteria in the algorithm; (4) the simplicity of the algorithm structure provides a convenient platform for implementing specific and sophisticated tracking criteria to meet specific needs; and (5) the user can fully control the performance of the algorithm by choosing values for the 11 well-defined tracking parameters