High-precision array element localization for vertical line arraysin the Arctic Ocean

Array element localization (AEL) surveys are often required to accurately localize acoustic instruments (transponders or sensors) in the ocean. These are typically based on transmitting or recording acoustic signals from or at a set of well-known positions. A significant limiting factor in many AEL surveys is the uncertainty inherent in these “known” positions. In this paper, an inversion algorithm is developed which properly treats both transponder and sensor positions as unknowns, subject to available a priori information in the form of position estimates and uncertainties. The algorithm essentially consists of an iterative linearized inversion of the raytracing equations employing the method of regularization. The approach is applied to independently localize transponders and vertical line array (VLA) sensors that form part of a three-dimensional sensor array in the Arctic Ocean. Confidence limits estimated via Monte Carlo simulation indicate that transponders and sensors are localized to less than 1 m in three dimensions. The VLA sensor motion, monitored over a seven-week period, appears to be predominately driven by tidal currents and is consistent with historical current measurements for the region     

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.     

Passive acoustic synthetic aperture processing techniques

Various parameters associated with the track of a stable CW source moving with constant velocity are estimated using synthetic aperture and Doppler processing techniques. These include the source frequency before Doppler distortion by its motion, the relative speed between the source and a constant velocity receiver, the range at closest approach to the source track, and the relative bearing to the source. Different processing techniques are suggested for a range of signal stabilities and observation times. Frequency analysis, or Doppler processing, supplements conventional synthetic aperture processing, and for relatively unstable signals a synthetic Doppler method is recommended. This method makes use of a rapid scan of signals from a succession of sensors in a horizontal line array to stimulate a higher speed motion of the array     

Depth measurement of remote sources using multipath propagation

A submerged acoustic source radiates narrowband Gaussian noise. Its signal propagates to a remote, large aperture vertical array over a multipath channel whose characteristics may or may not be fully known. The primary concern of this study is the accuracy of source depth estimates obtainable from the array output. Cramer-Rao bounds for the depth estimate are calculated. When the velocity profile is known exactly, the value of the bound is quite insensitive to the precise form of the velocity profile. A bound calculated from a constant velocity profile yields an excellent approximation for many situations likely to be encountered in practice. Introduction of an unknown parameter into the velocity profile has little effect on the Cramer-Rao bound for depth. However, a maximum likelihood estimator of depth working with an inaccurate value of the unknown parameter performs poorly. To obtain satisfactory performance, one must estimate the unknown parameters along with the source depth. Simulations demonstrate the success of this approach     

Spatial smoothing and minimum variance beamforming on data fromlarge aperture vertical line arrays

Various approaches to the beamforming of data from large aperture vertical line arrays are investigated. Attention is focused on the conventional beamforming problem where the angular power spectrum is estimated, in this case by the adaptive minimum variance processor. The data to be processed are 200 Hz CW transmissions collected at sea by a 900 m vertical line array with 120 equally spaced sensors. Correlated multipath arrivals result in signal cancellation for the adaptive processor, and spatial smoothing techniques must be used prior to beamforming. The processing of subapertures is proposed. Full aperture and subaperture processing techniques are used on the 200 Hz data. Multipath arrivals are found to illuminate only parts of the array, thus indicating that the wavefield can be highly inhomogeneous with depth     

Transiting aircraft parameter estimation using underwater acousticsensor data

Sound from an airborne source travels to a receiver beneath the sea surface via a geometric path that is most simply described using ray theory, where the atmosphere and the sea are assumed to be isospeed sound propagation media separated by a planar surface (the air-sea interface). This theoretical approach leads to the development of a time-frequency model for the signal received by a single underwater acoustic sensor and a time-delay model for the signals received by a pair of spatially separated underwater acoustic sensors. The validity of these models is verified using spatially averaged experimental data recorded from a linear array of hydrophones during various transits of a turboprop aircraft. The same approach is used to solve the inverse time-frequency problem, that is, estimation of the aircraft's speed, altitude, and propeller blade rate given the observed variation with time of the instantaneous frequency of the received signal. Similarly, the inverse time-delay problem is considered whereby the speed and altitude of the aircraft are estimated using the differential time-of-arrival information from each of two adjacent pairs of widely spaced hydrophones (with one hydrophone being common to each pair). It is found that the solutions to each of the inverse problems provide reliable estimates of the speed and altitude of the aircraft, with the inverse time-frequency method also providing an estimate that closely matches the actual propeller blade rate     

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     

Efficient Sensor Characteristic Selection for Cost-Effective Distributed Sensor Networks

For distributed sensor technologies whose costs are understood (or which may be estimated in some reasonable manner), we derive a simple analytic means by which to estimate the most cost-effective sensor detection range. Specifically, we consider design of sensor nodes whose purpose is to exploit a set of coherent acoustic array technologies to detect a target with a specified radiated signature in an environment characterized by the sonar equation. We define a simplified calculus of distributed search that exploits simple target motion as a means to enhance spatial coverage for a sparse field of uniformly distributed sensor nodes. We examine this strategy in the context of both area (two-dimensional) and volume (three-dimensional) surveillance coverage under both cylindrical and spherical spreading models. In all situations, cost-effective design guidance is given based on maintaining spatial detection coverage     

Multipath channel identification with wavelet packets

This paper deals with the basic modeling problem in underwater acoustics that is the characterization of the channel between a transmitter and a receiver. The problem is analyzed here using an array of sensors that receive PSK signals emitted by several sources. Data come from an experiment realized by a physical system situated in the Mediterranean Sea. In order to identify the multipath channel, we need to access the propagation time delay and the angle of arrival of each propagation ray. However, many of these acoustic ray paths are too close to be separated by classic processing methods (matched filter, beamforming, etc.); new methods with better resolution must be applied in order to analyze the experimental signals and to determine their arrival time on the array of sensors. After a presentation of this problem, we will first discuss high-resolution methods that are usually applied in the localization problem; we will then focus on wavelet packet analysis which provides good results by improving the temporal resolution of acoustic signals     

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     

Acoustic Detection and Localization of a Turboprop Aircraft by an Array of Hydrophones Towed Below the Sea Surface

The acoustic spectrum of a propeller-driven aircraft is dominated by a series of spectral lines that are harmonically related to the blade rate (which is equal to the product of the propeller rotation rate and the number of blades on the propeller). We show that an array of acoustic sensors towed below the sea surface can be used for the passive detection and localization of such an aircraft. The acoustic energy from an aircraft is found to reach the subsurface sensors via two propagation paths: a bottom reflection path that enables the aircraft to be detected at long ranges, and a direct path that is present only when the aircraft passes overhead. For each of these paths, the observed variation with horizontal range of the Doppler shift in the blade rate closely matches the variation predicted by the simple model presented in this paper. Good agreement between theory and experiment is also obtained for the variation with horizontal range of the aircraft's apparent bearing. Thus, by using the observed Doppler shift and apparent bearing information, we were able to estimate the aircraft's horizontal range, speed, direction, and altitude.      

Improved time-delay estimates of underwater acoustic signals usingbeamforming and prefiltering techniques

Passive sonar systems that localize broadband sources of acoustic energy estimate the difference in arrival times (or time delays) of an acoustic wavefront at spatially separated hydrophones, The output amplitudes from a given pair of hydrophones are cross-correlated, and an estimate of the time delay is given by the time lag that maximizes the cross correlation function. Often the time-delay estimates are corrupted by the presence of noise. By replacing each of the omnidirectional hydrophones with an array of hydrophones, and then cross-correlating the beamformed outputs of the arrays, the author shows that the effect of noise on the time-delay estimation process is reduced greatly. Both conventional and adaptive beamforming methods are implemented in the frequency domain and the advantages of array beamforming (prior to cross-correlation) are highlighted using both simulated and real noise-field data. Further improvement in the performance of the broadband cross-correlation processor occurs when various prefiltering algorithms are invoked     

Hypothesis grids: improving long baseline navigation for autonomous underwater vehicles

Navigation continues to fundamentally limit our ability to understand the underwater world. Long baseline navigation uses range measurements to localize a remote vehicle using acoustic time-of-flight estimates. For autonomous surveys requiring high precision navigation, current solutions do not satisfy the performance or robustness requirements. Hypothesis grids represent the survey environment capturing the spatial dependence of acoustic range measurement, providing a framework for improving navigation precision and increasing the robustness with respect to non-Gaussian range observations. Prior association probabilities quantify the measurement quality as a belief that subsequent observations will correspond to the direct-path, a multipath, or an outlier as a function of the estimated location. Such a characterization is directly applicable to Bayesian navigation techniques. The algorithm for creating the representation has three main components: Mixed-density sensor model using Gaussian and uniform probability distributions, measurement classification and multipath model identification using expectation-maximization (EM), and grid-based spatial representation. We illustrate the creation of a set of hypothesis grids, the feasibility of the approach, and the utility of the representation using survey data from the autonomous benthic explorer (ABE).     

Joint direction-of-arrival and array-shape tracking for multiplemoving targets

The problem of tracking the directions-of-arrival (DOAs) of multiple moving sonar targets with an array of passive sensors is complicated by sensor movement. An algorithm for the joint tracking of source DOAs and sensor positions is presented to address this problem. Initial maximum-likelihood estimates of source DOAs and sensor positions are refined by Kalman filtering. Spatio-temporally correlated array movement is considered. Source angle dynamics are used to achieve correct data association. The new technique is capable of performing well for the difficult cases of sources that cross in angle as well as for fully coherent sources. Computer simulations show that the approach is robust in the presence of array motion modeling uncertainty and effectively reduces dependence on expensive and possibly unreliable hardware     

A brief description of the fundamental difficulties in passive ranging

The use of passive sensors to estimate range and bearing to an acoustic source is investigated. The variance of the estimators is shown to depend on the number of sensors, integration time, signal-to-noise ratio, and more significantly, on the available array length. The variances for four different array configurations are discussed.     

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.     

Modal Inversion Analysis for Geoacoustic Properties of the New Jersey Continental Shelf in the SWAT Experiments

In this paper, inversion for bottom sediment properties at a site on the New Jersey continental shelf is studied as part of the Shallow Water Acoustic Technology (SWAT) project. A source towed at a constant water depth over a range of some tens of kilometers transmitted low-frequency continuous wave (cw) signals, which were measured on a bottom-moored vertical line array of receivers. For the along-shelf geometry, the zeroth-order asymptotic Hankel transform is then applied to the acoustic field at 50 Hz measured on the resulting synthetic aperture horizontal array created at each receiver depth. The resulting horizontal wave number spectra, which have peaks corresponding to the mode eigenvalues, are observed to have slightly different values at different receiver depths, and therefore, stochastic mode inversion is exploited to utilize all of the observed peak position information. The estimated sound-speed profile (SSP) for the upper 10 m of sediment is then compared with an inversion result obtained using midfrequency (2–16 kHz) chirp sonar pulses reflected at normal incidence from the sediment. Although obtained using totally different inversion techniques, both estimated profiles are shown to be in good agreement in the top 10 m of sediment. The acoustic field simulated using the inverted SSP also agrees well with the measured acoustic field at each receiver depth. Furthermore, simulated sound fields which use this profile as input data are shown to be effective in predicting the measurements obtained at a different frequency (125 Hz) and for a different (cross-shelf) geometry.      

Acoustic positioning for an array of freely drifting infrasonic sensors

Initial testing of the prototype element of a freely drifting infrasonic sensor array is described. The intent of this measurement system is to gather wide aperture data sets which will be used both to characterize ambient noise in the region 1-10 Hz and to assess the gains possible from beam forming utilizing a collection of very low frequency (VLF) sensors. Coherent processing (beam forming) of the infrasonic sensor data is made possible by relative position measurements derived from mutual acoustic interrogation of the elements at a higher frequency. Surface echo data from a recent sea test of the prototype buoy are used to illustrate the type of pulse processing which will be implemented as a first step in the localization procedure.     

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.     

Limitations on the overlap-correlator method imposed by noise andsignal characteristics

Limitations on the performance of the overlap-correlator method of forming a passive synthetic aperture are derived. The technique uses the overlap of the array in sequential positions to estimate a series of phase correction factors that compensate for the motion of the array over time. It is of primary interest to optimize this overlap with respect to the effects of random noise. By minimizing the variance of the estimates of the set of phase correction factors, it is found that the optimal overlap is one-half the length of the physical array. Using this optimal overlap, the bounds on the usable spatial response are then determined as a function of signal-to-noise ratio and the number of hydrophones in the physical array. The ability of the overlap-correlator algorithm to synthesize a coherent aperture is investigated for the case of multiple sources in the absence of noise