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Multipath arrivals are identified and extracted from midfrequency impulse responses at a vertical line array produced by a broadband source transmitting linearly frequency modulated pulses in the SBCEX 17 experiment. Arrival times are extracted from received data using particle filtering and smoothing. Specifically, sequential filtering is applied to the received time series at sixteen phones for the estimation of three paths generated by sound interacting with the propagation medium. This is followed up with a smoother that provides “crisp” arrival time probability densities. A peak-finding method is used to identify a fourth path. The estimated arrival times obtained by the process above are linked with a sound propagation model based on ray tracing and linearization for estimation of source location and water column depth and sound speed. An exhaustive search follows for inversion for sediment sound speed and thickness. Because the source is moving, receptions are available on a track and arrival time estimation and corresponding inversion are performed at every source location within the track. The unknown parameters are estimated sequentially with two approaches. Approach one is linearization using prior information from one location propagated to the next. Approach two relies on a second particle filter, capturing the dynamic evolution of parameters along the track. Both techniques lead to sediment property estimation. Results from the two methods agree, pointing to robustness in inversion when impulse responses and arrival times estimated from those are employed as input to the inverse problem. [ABSTRACT FROM AUTHOR]

The estimation of ship source levels (SSLs) in shallow-water environments can be complicated by sound interaction with the seabed. Uncertainty in seabed properties influences SSL estimates, and it is of interest to mitigate and quantify such effects. This article proposes a probabilistic approach to ship radiated noise recorded on a vertical line array (VLA) of hydrophones to infer SSL and properties of a mud-sand shallow water seabed on the New England Shelf. The approach, trans-dimensional Bayesian marginalization, samples probabilistically over complex spectral source strengths, source depths/ranges, and number of seabed layers and geoacoustic parameters of each layer. The Bayesian information criterion is applied to determine the appropriate number of (point) sources used to describe a ship. Radiated noise due to two merchant ships passing the VLA at beam aspect at 3.2−3.4-km range is considered. The SSL estimates agree well with reference spectra from shallow-water studies on large ensembles of merchant ships. The average SSL uncertainty (in terms of one-half the interquartile range interval) is 3.2 dB/Hz for low-frequency narrowband (20−120 Hz) and 1.8 dB/Hz for broadband noise (190−590 Hz). Seabed layering and geoacoustic parameter estimates agree reasonably well with mud-over-sand seabed models from other inversions in the area. [ABSTRACT FROM AUTHOR]

Acoustic recordings of signals in the 1.5–4.0-kHz band were analyzed for information about the sound speed and attenuation frequency dispersion of a fine-grained sediment found in the New England Mudpatch. Analysis of piston cores established prior bounds for a geophysical parameterization of a seabed model that predicts Kramers–Kronig dispersion relations. Sediment layers are described by the Buckingham viscous grain shearing (VGS) model that accounts for the effects of overburden pressure of compressional and shear speeds and attenuations. A statistical inverse problem was solved by using multiple samples of received levels recorded on two vertical line arrays as a function time and hydrophone depth for six frequencies in the 1.5–4.0-kHz band. A statistical inference model that assumed both model parameters and data samples are random variables quantified information content from marginalization of a conditional posterior probability distribution for the geophysical parameters that characterize the mud layer. From the inferred geophysical parameter point estimates the sediment sound speed and attenuation frequency dispersion are predicted and compared to previously reported direct measurements. Also, the predicted sound-speed gradient in the mud sediment from the VGS model is compared to a previous inference that utilized explosive sources. [ABSTRACT FROM AUTHOR]

For a sound field observed on a sensor array, performance of conventional high-resolution adaptive beamformers is affected dramatically in the presence of coherent multipath signals, but the directions-of-arrival (DOAs) and power levels of these arrivals can be resolved with compressed sensing (CS). When the number of multipath signals is sufficiently small, a CS approach can be used by formulating the problem as a sparse signal recovery problem. CS overcomes the difficulty of resolving coherent arrivals at an array by directly processing the sensor outputs without first estimating a sensor covariance matrix. CS is compared to the adaptive minimum-variance-distortionless-response (MVDR) spatial processor with spatial smoothing. Though spatial smoothing produces improved results by preprocessing the sensor array covariance matrix to decorrelate the coherent multipath components, it reduces the effective aperture of the array and hence reduces the resolution. An empirical study with a uniform linear array (ULA) demonstrates that CS outperforms MVDR beamformer with spatial smoothing in terms of spatial resolution and bias and variance of DOA and power estimates. Analysis of the shallow-water HF97 ocean acoustic experimental data shows that CS is able to recover the DOAs and power levels of the multipath signals with superior resolution compared to MVDR with spatial smoothing. [ABSTRACT FROM AUTHOR]

Covariance matrices of noise models are used in signal and array processing to study the effect of various noise fields and array configurations on signals and their detectability. Here, the asymptotic eigenvalues of noise covariance matrices in 2-D and 3-D attenuating media are derived. The asymptotic eigenvalues are given by a continuous function, which is the Fourier transform of the infinite sequence formed by sampling the spatial coherence function. The presence of attenuation decreases the value of the large eigenvalues and raises the value of the smaller eigenvalues (compared to the attenuation free case). The eigenvalue density of the sample covariance matrix also shows variation in shape depending on the attenuation, which potentially could be used to retrieve medium attenuation properties from observations of noise. [ABSTRACT FROM PUBLISHER]

Radar clutter in a non-standard atmosphere usually is modeled based on a single grazing angle at each range. Instead, the angular distribution of incident power can be used to obtain a more accurate model of the clutter. Angular spectral estimation provides the grazing angle distribution of propagating power. However, a large gradient in the refractivity profile, e.g., an evaporation duct, distorts plane wave propagation which in turn violates assumptions of plane wave spectral estimation. Ray tracing is used in these situations, but has its own limitations (e.g., shadow zones). We suggest using curved wave spectral estimation (CWS) that yields reliable results for any refractivity profile, in contrast to plane wave spectral estimation. CWS is used to derive multiple grazing angle clutter, a model for ocean surface clutter in the microwave region that depends on all incident angles at each range and their corresponding powers. [ABSTRACT FROM PUBLISHER]

The asymptotic eigenvalues are derived for the true noise covariance matrix (CM) and the noise sample covariance matrix (SCM) for a line array with equidistant sensors in an isotropic noise field. In this case, the CM in the frequency domain is a symmetric Toeplitz sinc matrix which has at most two distinct eigenvalues in the asymptotic limit of an infinite number of sensors. Interestingly, for line arrays with interelement spacing less than half a wavelength, the CM turns out to be rank deficient. The asymptotic eigenvalue density of the SCM is derived using random matrix theory (RMT) for all ratios of the interelement spacing to the wavelength. When the CM has two distinct eigenvalues, the eigenvalue density of the SCM separates into two distinct lobes as the number of snapshots is increased. These lobes are centered at the two distinct eigenvalues of the CM. The asymptotic results agree well with analytic solutions and simulations for arrays with a small number of sensors. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce the addition of an iterative, successive interference cancellation (SIC) process to improve on a multiuser, single-input–multiple-output (SIMO) communications receiver using passive time reversal as a space-time preprocessor. Time reversal has been shown to apply the spatial degrees of freedom to enhance the signal-to-noise ratio (SNR) and suppress interference for a target user. With the introduction of SIC, the receiver can remove the residual interference experienced by each user while preserving the SNR gain achieved by time-reversal preprocessing. The SIC process is a decision-directed approach for removing multiuser interference at the receiver and is similar to the decision-feedback equalizer (DFE) for intersymbol interference (ISI) channels. The interference experienced by each user is estimated at the receiver using previously decoded symbols from interfering users. This estimate is scaled and synchronized before subtraction from the target user's signal after time-reversal combining. Since SIC is applied before symbol decoding, symbol estimates are improved as the process is allowed to iterate until a stationary point is reached. Following time-reversal combining and SIC, a DFE can mitigate any remaining ISI before symbol decisions are made. Data collected from two Focused Acoustic Fields experiments (FAF-05 and FAF-06) are used to demonstrate the performance of the proposed interference cancellation scheme. During the FAF-05 experiment, three users transmitted 16-quadrature amplitude modulation (QAM) symbols simultaneously over the 3–4-kHz frequency band to a 20-element receiving array deployed in 120-m-deep water at a range of 20 km. The FAF-06 experiment included the simultaneous transmissions of 8-QAM symbols from two users over the 9–21-kHz band to a 16-element receiving array in 92-m-deep water at a range of 2.2 km. For both of the examples, SIC is shown to improve the output SNR in the presence of strong interference over time-reversal processing alone. This translates to a significant bit error rate (BER) reduction from 1.53\times 10^-2 to 8.80\times 10^-4 for the FAF-05 data and from 1.77\times 10^-3 to error-free decoding for the FAF-06 data. [ABSTRACT FROM PUBLISHER]

This paper presents inversion results of the 2006 Shallow Water Experiment (SW06) data measured on a vertical line array. A low-frequency (100–900 Hz) chirp source was towed along two tracks (circle, straight line) at 30-m depth. For the inversions, a three-step optimization scheme is applied to the data using very fast simulated reannealing (VFSR). The objective function is defined by the energy of the backpropagated signal from the array to the source. At each step, water-column sound-speed profile (SSP), experimental geometry, and geoacoustic parameters are inverted successively. An environmental model is employed consisting of a linear segmented SSP in the water column, a sediment layer, and a half-space. The geometric parameter inversion results show good agreement with in situ measurements. Finally, the estimated geoacoustic parameters show that the experimental site near the vertical line array (VLA) is fairly homogeneous in bottom properties consisting of a 21-m-thick sediment layer with sound speed of around 1600 m/s over a hard basement whose sound speed is approximately 1750 m/s. [ABSTRACT FROM AUTHOR]

In this paper, we present an iterative approach for recovering information sent over a shallow underwater acoustic (UWA) communication channel. The procedure has three main tasks: estimation of channel model parameters (CMPs), channel equalization, and decoding. These tasks are performed cyclicly until the algorithm converges. Information bits are convolutionally encoded, punctured and permuted, mapped into quaternary phase-shift keying (QPSK) symbols, linearly modulated, and transmitted through a downward-refracting ocean waveguide. Training symbols are prepended to the transmitted sequence for initial estimation of CMPs. Our algorithm processes data from a single receive sensor. Data are received on a vertical array and the performance of the algorithm for each sensor in the array is examined. There is negligible Doppler spread in the received data. However, difference between transmitter and receiver clocks as well as slight motion of the receive array produce a nonnegligible compression of the received signals. Consequently, there is observable Doppler "shift." Nonuniform resampling of the data produces time series we model as the output of a linear time-invariant system. Resampling and CMP estimation are done iteratively, in conjunction with equalization and decoding. The algorithm successfully processes the data to yield few or no information bit errors. [ABSTRACT FROM AUTHOR]

We address the problem of tracking the spatial and temporal lower atmospheric variations in maritime environments. The evolution of the range and height-dependent index of refraction is tracked using the sea clutter return from sea-borne radars operating in the region. A split-step fast Fourier transform based parabolic equation approximation to the wave equation is used to compute the clutter return in complex environments with varying index of refraction. In addition, regional statistics are incorporated as prior densities, resulting in a highly nonlinear and non-Gaussian tracking problem. Tracking algorithms such as the extended Kalman, unscented Kalman and particle filters are used for tracking both evaporative and surface-based electromagnetic ducts frequently encountered in marine environments. The tracking performances and applicability of these techniques to different types of refractivity-from-clutter problems are studied using the posterior Cramér-Rao lower bound. Track divergence statistics are analyzed. The results show that while the tracking performance of the Kalman filters is comparable to the particle filters in evaporative duct tracking, it is limited by the high non-linearity of the parabolic equation for the surface-based duct case. Particle filters, on the other hand, prove to be very promising in tracking a wide range of environments including the abruptly changing ones. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper describes a Markov chain Monte Carlo (MCMC) sampling approach for the estimation of not only the radio refractivity profiles from radar clutter but also the uncertainties in these estimates. This is done by treating the refractivity from clutter (RFC) problem in a Bayesian framework. It uses unbiased MCMC sampling techniques, such as Metropolis and Gibbs sampling algorithms, to gather more accurate information about the uncertainties. Application of these sampling techniques using an electromagnetic split-step fast Fourier transform parabolic equation propagation model within a Bayesian inversion framework can provide accurate posterior probability distributions of the estimated refractivity parameters. Then these distributions can be used to estimate the uncertainties in the parameters of interest. Two different MCMC samplers (Metropolis and Gibbs) are analyzed and the results compared not only with the exhaustive search results but also with the genetic algorithm results and helicopter refractivity profile measurements. Although it is slower than global optimizers, the probability densities obtained by this method are closer to the true distributions. [ABSTRACT FROM AUTHOR]

Geoacoustic inversion results based on data obtained during the Asian Seas International Acoustics Experiment (ASIAEX) 2001 East China Sea experiment are reported. The inversion process uses a genetic-algorithm-based matched-field-processing approach to optimize the search procedure for the unknown parameters. Inversion results include both geometric and geoacoustic variables. To gauge the quality of the inversion, two different analyses are employed. First, the inversion results based upon discrete source-receiver ranges are confirmed by continuous source localization over an interval of time. Second, separate inversions at many different ranges are carried out and the uncertainties of the parameter estimation are analyzed. The analysis shows that both methods yield consistent results, ensuring the reliability of inversion in this study. [ABSTRACT FROM AUTHOR]

Estimation of the atmospheric refractivity is important for the prediction of radar performance. Surface or elevated trapping layers formed by the outflow of relatively dry and warm air over a cooler body of water often result in the refractive structure-supporting-convergence-zone-like behavior and multimodal effects. The propagation under such conditions can be very sensitive to even small changes in the vertical and horizontal structure of refractivity. Obtaining in situ measurements of sufficient fidelity to estimate where intensifications in the electromagnetic field will occur is difficult. The authors previously have demonstrated the ability to infer refractivity parameters from grazing-incidence radar sea-clutter data. The radar system was the 2.8-GHz space range radar that overlooks the Atlantic Ocean in the vicinity of Wallops Island, VA. The forward modeling consisted of the mapping of an 11-parameter environmental model via an electromagnetic propagation model into the space of the radar clutter observations. A genetic algorithm was employed to optimize the objective function. Ground truth data were atmospheric soundings obtained by a helicopter flying a saw-tooth pattern. The overall result was that the ability to estimate the propagation within the duct itself was comparable to that of in situ measurements. However, the ability to characterize the region above the duct was quite poor. Modern three--dimensional radars, however, have relatively narrow beams. Using these narrow beams at multiple elevations might resolve the ambiguity leading to the poor characterization in the region above the duct. Using radar data from the SPANDAR radar, it is demonstrated that such an approach is feasible and that more-robust estimates can... [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Presents a study conducted to determine if adaptive beamforming is feasible on a turning array of a tow ship. Theoretical background; Methodology; Results and discussion.

Presents a study that investigated an initial demonstration of underwater acoustic communication using time reversal. Discussion of the theory of time reversal; Experimental results.