Sensor Array Processing with Manifold Uncertainty

<p>The spatial spectrum, also known as a field directionality map, is a description of the spatial distribution of energy in a wavefield. By sampling the wavefield at discrete locations in space, an estimate of the spatial spectrum can be derived using basic wave propagation models. The observable data space corresponding to physically realizable source locations for a given array configuration is referred to as the array manifold. In this thesis, array manifold ambiguities for linear arrays of omni-directional sensors in non-dispersive fields are considered. </p><p>First, the problem of underwater a hydrophone array towed behind a maneuvering platform is considered. The array consists of many hydrophones mounted to a flexible cable that is pulled behind a ship. The towed cable will bend or distort as the ship performs maneuvers. The motion of the cable through the turn can be used to resolve ambiguities that are inherent to nominally linear arrays. The first significant contribution is a method to estimate the spatial spectrum using a time-varying array shape in a dynamic field and broadband temporal data. Knowledge of the temporal spectral shape is shown to enhance detection performance. The field is approximated as a sum of uncorrelated planewaves located at uniform locations in angle, forming a gridded map on which a maximum likelihood estimate for broadband source power is derived. Uniform linear arrays also suffer from spatial aliasing when the inter-element spacing exceeds a half-wavelength. Broadband temporal knowledge is shown to significantly reduce aliasing and thus, in simulation, enhance target detection in interference dominated environments. </p><p>As an extension, the problem of towed array shape estimation is considered when the number and location of sources are unknown. A maximum likelihood estimate of the array shape using the field directionality map is derived. An acoustic-based array shape estimate that exploits the full 360$^\circ$ field via field directionality mapping is the second significant contribution. Towed hydrophone arrays have heading sensors in order to estimate array shape, but these sensors can malfunction during sharp turns. An array shape model is described that allows the heading sensor data to be statistically fused with heading sensor. The third significant contribution is method to exploit dynamical motion models for sharp turns for a robust array shape estimate that combines acoustic and heading data. The proposed array shape model works well for both acoustic and heading data and is valid for arbitrary continuous array shapes.</p><p>Finally, the problem of array manifold ambiguities for static under-sampled linear arrays is considered. Under-sampled arrays are non-uniformly sampled with average spacing greater than a half-wavelength. While spatial aliasing only occurs in uniformly sampled arrays with spacing greater than a half-wavelength, under-sampled arrays have increased spatial resolution at the cost of high sidelobes compared to half-wavelength sampled arrays with the same number of sensors. Additionally, non-uniformly sampled arrays suffer from rank deficient array manifolds that cause traditional subspace based techniques to fail. A class of fully agumentable arrays, minimally redundant linear arrays, is considered where the received data statistics of a uniformly spaced array of the same length can be reconstructed in wide sense stationary fields at the cost of increased variance. The forth significant contribution is a reduced rank processing method for fully augmentable arrays to reduce the variance from augmentation with limited snapshots. Array gain for reduced rank adaptive processing with diagonal loading for snapshot deficient scenarios is analytically derived using asymptotic results from random matrix theory for a set ratio of sensors to snapshots. Additionally, the problem of near-field sources is considered and a method to reduce the variance from augmentation is proposed. In simulation, these methods result in significant average and median array gains with limited snapshots.</p>Dissertatio

Detection, classification and localization of seabed objects with a virtual time reversal mirror

Thesis (S.M.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2009.Includes bibliographical references (p. 88-91).The work presented in this thesis addresses the problem of the detection, classification and localization of seabed objects in shallow water environments using a time reversal approach in a bistatic configuration. The waveguide is insonified at low frequency ('kHz) with an omnidirectional source and the resulting scattered field is sampled by a receiving array towed behind an Autonomous Underwater Vehicle (AUV). The recorded signals are then processed to simulate onboard the AUV, the time reversed transmissions which serve to localize the origin of the scattered field on the seabed and estimate the position of the targets present. The clutter rejection based upon the analysis of the singular values of the Time Reversal operator is investigated with simulated data and field measurements collected off the coast of Palmaria (Italy) in January 2008.by Alexis J. Dumortier.S.M

Efficient inversion methods in underwater acoustics

This dissertation describes efficient methods developed and implemented for source localization and sound speed and bottom depth estimation using sound propagation in the ocean. The proposed inversion techniques are based on the linearization of the generally non-linear inverse problem of parameter estimation in underwater acoustics. These techniques take into account properties of the ocean environment and are accurate in their estimation results without being prohibitively computationally intensive. For the inversion, select ray paths are taken into account: the direct, first surface bounce, and first bottom bounce. Ray travel time derivatives with respect to parameters that affect path arrival times are obtained analytically. These derivatives and a first order expansion are then used to find estimates of unknown parameters through replica and true paths; replica paths are generated using ray theory for underwater sound propagation and true paths are identified from measured time series. The linearization scheme works efficiently for the estimation of geometric parameters such as the source and receiver location coordinates and the depth of the water column. It is also successful in estimating the sound speed profile in the ocean using empirical orthogonal functions. In this work, the linearization inversion technique is applied to marine mammal tracking, and it is also used with real data collected during the Haro Strait experiment for source and receiver localization. For the Haro Strait data, inversion using linearization is also compared to matched-field processing, which estimates source location and geoacoustic parameters through a full field matching approach

The measurement of underwater acoustic noise radiated by a vessel using the vessel's own towed array

The work described in this thesis tested the feasibility of using a towed array of hydrophones to: 1. localise sources of underwater acoustic noise radiated by the towvessel, 2. determine the absolute amplitudes of these sources, and 3. determine the resulting far-field acoustic signature of the tow-vessel. The concept was for the towvessel to carry out a U-turn manoeuvre so as to bring the acoustic section of the array into a location suitable for beamforming along the length of the tow-vessel. All three of the above were shown to be feasible using both simulated and field data, although no independent field measurements were available to fully evaluate the accuracy of the far-field acoustic signature determinations. A computer program was written to simulate the acoustic signals received by moving hydrophones. This program had the ability to model a variety of acoustic sources and to deal with realistic acoustic propagation conditions, including shallow water propagation with significant bottom interactions. The latter was accomplished using both ray and wave methods and it was found that, for simple fluid half-space seabeds, a modified ray method gave results that were virtually identical to those obtained with a full wave method, even at very low frequencies, and with a substantial saving in execution time. A field experiment was carried out during which a tug towing a 60-hydrophone array carried out a series of U-turn manoeuvres. The signals received by the array included noise radiated by the tow-vessel, signals from acoustic tracking beacons mounted on the tow-vessel, and transient signals generated by imploding sources deployed from a second vessel.Algorithms were developed to obtain snapshots of the vertical plane and horizontal plane shapes of the array from the transient data and to use range data derived from the tracking beacon signals to track the hydrophones in the horizontal plane. The latter was complicated by a high proportion of dropouts and outliers in the range data caused by the directionality of the hydrophones at the high frequencies emitted by the beacons. Despite this, excellent tracking performance was obtained. Matched field inversion was used to determine the vertical plane array shapes at times when no transient signals were available, and to provide information about the geoacoustic properties of the seabed. There was very good agreement between the inversion results and array shapes determined using transient signals. During trial manoeuvres the array was moving rapidly relative to the vessel and changing shape. A number of different array-processing algorithms were developed to provide source localisation and amplitude estimates in this situation: a timedomain beamformer; two frequency-domain, data independent beamformers; an adaptive frequency-domain beamformer; and an array processor based on a regularised least-squares inversion. The relative performance of each of these algorithms was assessed using simulated and field data. Data from three different manoeuvres were processed and in each case a calibrated source was localised to within 1 m of its known position at the source's fundamental frequency of 112 Hz.Localisation was also successful in most instances at 336 Hz, 560 Hz and 784 Hz, although with somewhat reduced accuracy due to lower signal to noise ratios. Localisation results for vessel noise sources were also consistent with the positions of the corresponding items of machinery. The estimated levels of the calibrated source obtained during the three manoeuvres were all within 4.1 dB of the calibrated value, and varied by only 1.3 dB between manoeuvres. Results at the higher frequencies had larger errors, with a maximum variation of 3.8 dB between serials, and a maximum deviation from the calibrated value of 6.8 dB. An algorithm was also developed to predict the far-field signature of the tow-vessel from the measured data and results were produced. This algorithm performed well with simulated data but no independent measurements were available to compare with the field results

Introducing passive matched field acoustic tomography

In acoustic tomography sea-basin environmental parameters such as temperature profiles and current-velocities are derived, when ray propagation models are adopted, by the travel time estimates relative to the identifiable ray paths. The transmitted signals are either single frequency, or impulsive, or intermittent and deterministic. When the wavelength is comparable with the scale lengths present in the propagation scenario, Matched Field Tomography (MFT) is used, entailing the consideration of waveguide modes instead of rays. A new concept in tomography is introduced in the paper, that employs passively the noise emitted by ships of opportunity (cargoes, ferries) as source signals. The passive technique is acoustic-pollution-free, and if a basin is selected in which a regular ship traffic occurs data can be received on a regular schedule, with no transmission cost. A novel array pre-processor for passive tomography is introduced, such that the signal structure at the pre-processor output is nearly the same as that obtainable in the case of single-frequency source signals. Hence, at the pre-processor output all the tomographic inversion methods valid for active tomography employing single-frequency sources can be applied. The differences between active and passive tomography are pointed out and the potential of passive techniques is illustrated by simple propagation scenarios adopting either rays or waveguide modes